Dissertations / Theses: 'Multispectral imagery'

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Lone, Lars O. "Airborne hyperspectral and satellite multispectral imagery of the Mississippi Gulf Coast region." Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FLone.pdf.

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Thesis (M.S. in Physical Oceanography)--Naval Postgraduate School, December 2006. Thesis Advisor(s): Robin Tokmakian. "December 2006." Includes bibliographical references (p. 73-75). Also available in print.

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Sandersfeld, Michelle R. "Detection of Subpixel Submerged Mine-Like Targets in WorldView-2 Multispectral Imagery." Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/17458.

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Approved for public release; distribution is unlimited The utility of satellite spectral imagery is analyzed for the detection of submerged mine like objects. The targets that were utilized were sub-meter in size and emplaced in the water off the coast of La Jolla, California for a barnacle study. There were three surface targets and three submerged targets that did not exceed three meters in depth. Two meter multispectral and half meter panchromatic WorldView-2 data were used for image processing and analysis. The multispectral data proved more useful than the higher spatial resolution panchromatic data (sub-pixel vs resolved).For the multispectral data, principal component analysis was the most successful of the techniques, locating the submerged and surface targets. Attempts to use the RX-UTD anomaly detector were less successful, because of excessive false positives. This study supports the concept that commercial remote sensing is a viable option to support mine countermeasures.

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Barron, John P. "An objective technique for Arctic cloud analysis using multispectral AVHRR satellite imagery." Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/23335.

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Approved for public release; distribution is unlimited. An established cloud analysis routine has been modified for use in the Arctic. The separation of clouds from the snow and sea ice backgrounds is accomplished through a multispectral technique which utilizes VHRR channel 2 (visible), channel 3 (near infrared) and channel 4 (infrared) data. The primary means of cloud identification is based on a derived channel 3 reflectance image. At this wavelength, a significant contrast exists between liquid clouds and the arctic backgrounds, unlike in the standard visible and infrared images. The channel 3 reflectance is obtained by first using the channel 4 emission temperature to estimate the thermal emission component of the total channel 3 radiance. This thermal emission component is subsequently removed from the total radiance, leaving only the solar reflectance component available for analysis. Since many ice clouds do not exhibit a substantially greater reflectance is channel 3, the routine exploits differences in transmissive characteristics between channels 3 and 4 for identification. The routine was applied to six case studies which had been analyzed by three independent experts to establish 'ground truth'. Verification of the cloud analysis results, through a comparison to the subjective analyses, yielded impressive statistics. A success rate of 77.9% was obtained with an arguably small data base of 131 undisputed scenes http://archive.org/details/objectivetechniq00barr Lieutenant, United States Navy

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Viau, Claude. "Multispectral Image Analysis for Object Recognition and Classification." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34532.

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Computer and machine vision applications are used in numerous fields to analyze static and dynamic imagery in order to assist or automate some form of decision-making process. Advancements in sensor technologies now make it possible to capture and visualize imagery at various wavelengths (or bands) of the electromagnetic spectrum. Multispectral imaging has countless applications in various field including (but not limited to) security, defense, space, medical, manufacturing and archeology. The development of advanced algorithms to process and extract salient information from the imagery is a critical component of the overall system performance. The fundamental objectives of this research project were to investigate the benefits of combining imagery from the visual and thermal bands of the electromagnetic spectrum to improve the recognition rates and accuracy of commonly found objects in an office setting. The goal was not to find a new way to “fuse” the visual and thermal images together but rather establish a methodology to extract multispectral descriptors in order to improve a machine vision system’s ability to recognize specific classes of objects.A multispectral dataset (visual and thermal) was captured and features from the visual and thermal images were extracted and used to train support vector machine (SVM) classifiers. The SVM’s class prediction ability was evaluated separately on the visual, thermal and multispectral testing datasets. Commonly used performance metrics were applied to assess the sensitivity, specificity and accuracy of each classifier. The research demonstrated that the highest recognition rate was achieved by an expert system (multiple classifiers) that combined the expertise of the visual-only classifier, the thermal-only classifier and the combined visual-thermal classifier.

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Hodgson, Lucien Guy, and n/a. "Cotton crop condition assessment using arial video imagery." University of Canberra. Applied Science, 1991. http://erl.canberra.edu.au./public/adt-AUC20060725.144909.

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Cotton crop condition was assessed from an analysis of multispectral aerial video imagery. Visible-near infrared imagery of two cotton fields was collected towards the end of the 1990 crop. The digital analysis was based on image classification, and the accuracies were assessed using the Kappa coefficient of agreement. The earliest of three images proved to be best for distinguishing plant variety. Vegetation index images were better for estimating potential yield than the original multispectral image; so too were multi-channel images that were transformed using vegetation indices or principal component analysis. The seedbed preparation rig used, the nitrogen application rate and three plant varieties, a weed species and two cotton cultivars, could all be discriminated from the imagery. Accuracies were moderate for the discrimination of plant variety, tillage treatment and nitrogen treatment, and low for the estimation of potential yield.

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Weber, François. "Modélisation de fonds multispectraux texturés et hétérogènes pour la détection d'anomalies." Electronic Thesis or Diss., Paris, ENST, 2017. http://www.theses.fr/2017ENST0033.

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Des méthodes de détection d’objets camouflés sont utilisées dans de nombreux domaines, dont celui de l’exploration de théâtres d’opérations militaires. Dans ce contexte, les spécificités des cibles à repérer ne sont pas connues a priori. Les méthodes de détection d’anomalies permettent de se passer de ces informations et forment le point de départ de cette thèse. Les données considérées dans ces travaux sont des images multispectrales de fonds naturels contenant des cibles camouflées. Ces fonds présentent un fort aspect texturé du à la végétation. Nous proposons d’exploiter conjointement les informations spectrale et spatiale dans le but de mesurer le gain conféré par la prise en compte des textures dans le cadre d’une détection d’anomalies. En effet, le taux de faux-positifs est susceptible d’augmenter sur des scènes très texturées si ces comportements ne sont pas prévus par le détecteur d’anomalies utilisé. Plusieurs méthodes de détection adaptées aux fonds multispectraux texturés ont été comparées à des détecteurs d’anomalies de référence n’exploitant que l’information spectrale. Les premiers détecteurs proposés reposent sur des modèles de type champs de Gauss-Markov aléatoires et mélanges de gaussiennes structurées, permettant des tests paramétriques ; les seconds sur des tests nonparamétriques dans des espaces à noyaux. Les résultats obtenus montrent la nécessité d’une segmentation conjointe à la détection d’anomalies sur des images hétérogènes. Par ailleurs, les meilleurs résultats de détection ont été obtenus grâce aux modèles dépourvus d’à priori sur les distributions des pixels de fonds Detection methods for spotting covered up objects are used in many fields of applications, including the exploration of millitary battlefields. In this context, no specification about what to detect can be known a priori. Anomaly detection methods can deal without these informations and are the starting point of this thesis. In this work, the considered data are multispectral images of natural scenes containing covered up targets. The vegetation present in these backgrounds causes strong textured aspects. We propose to exploit simultaneously both spectral and spatial informations to measure the gain obtained by considering the textures within an anomaly detection method. As a matter of fact, the false-positive rate is prone to increase on highly textured scenes if this kind of behaviour are not expected by the considererd anomaly detector. Several anomaly detection methods adapted to multispectral backgrounds have been compared to reference detectors that only exploit the spectral information. The first anomaly detectors we propose rely on models like Gaussian Markovian random fields and mixtures of structured Gaussian, allowing parametric tests ; the second ones rely on non-parametric tests operated in kernel-spaces. The obtained results show the necessisty of a joint segmentation and detection for heterogeneous scenes. Moreover, the best result have been obtained through anomaly detectors that do not assume any a priori distribution over data

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Rydberg, Anna. "Multispectral image analysis for extraction of remotely sensed features in agricultural fields /." Uppsala : Centre for Image Analysis, Swedish Univ. of Agricultural Sciences (Centrum för bildanalys, Sveriges lantbruksuniv.), 2001. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=009768972&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Nguyen, Tien Hoang. "Development of transformation method of multispectral imagery into hyperspectral imagery for detailed identification of metal and geothermal resources-related minerals." Kyoto University, 2017. http://hdl.handle.net/2433/227611.

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Karim, Zulfiqar. "Detection of search and rescue targets in digitised multispectral imagery using artificial neural networks." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0002/MQ42640.pdf.

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Olthof, Ian. "Development of a forest health index using high-resolution remotely-sensed multispectral digital imagery." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0017/MQ48405.pdf.

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Francis, John W. "Pixel-by pixel reduction of atmospheric haze effects in multispectral digital imagery of water /." Online version of thesis, 1989. http://hdl.handle.net/1850/11359.

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Olthof, Ian Carleton University Dissertation Geography. "Development of a forest health index using high-resolution remotely- sensed multispectral digital imagery." Ottawa, 1999.

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Higbee, Shawn. "A Bayesian approach to identification of gaseous effluents in passive LWIR imagery /." Online version of thesis, 2009. http://hdl.handle.net/1850/10969.

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Maier, Kathrin. "Direct multispectral photogrammetry for UAV-based snow depth measurements." Thesis, KTH, Geoinformatik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254566.

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Due to the changing climate and inherent atypically occurring meteorological events in the Arctic regions, more accurate snow quality predictions are needed in order to support the Sámi reindeer herding communities in northern Sweden that struggle to adapt to the rapidly changing Arctic climate. Spatial snow depth distribution is a crucial parameter not only to assess snow quality but also for multiple environmental research and social land use purposes. This contrasts with the current availability of affordable and efficient snow monitoring methods to estimate such an extremely variable parameter in both space and time. In this thesis, a novel approach to determine spatial snow depth distribution in challenging alpine terrain is presented and tested during a field campaign performed in Tarfala, Sweden in April 2019. A multispectral camera capturing five spectral bands in wavelengths between 470 and 860 nanometers on board of a small Unmanned Aerial Vehicle is deployed to derive 3D snow surface models via photogrammetric image processing techniques. The main advantage over conventional photogrammetric surveys is the utilization of accurate RTK positioning technology that enables direct georeferencing of the images, and thus eliminates the need for ground control points and dangerous and time-consuming fieldwork. The continuous snow depth distribution is retrieved by differencing two digital surface models corresponding to the snow-free and snow-covered study areas. An extensive error assessment based on ground measurements is performed including an analysis of the impact of multispectral imagery. Uncertainties and non-transparencies due to a black-box environment in the photogrammetric processing are, however, present, but accounted for during the error source analysis. The results of this project demonstrate that the proposed methodology is capable of producing high-resolution 3D snow-covered surface models (< 7 cm/pixel) of alpine areas up to 8 hectares in a fast, reliable and cost-efficient way. The overall RMSE of the snow depth estimates is 7.5 cm for data acquired in ideal survey conditions. The proposed method furthermore assists in closing the scale gap between discrete point measurements and regional-scale remote sensing, and in complementing large-scale remote sensing data by providing an adequate validation source. As part of the Swedish cooperation project ’Snow4all’, the findings of this project are used to support and validate large-scale snow models for improved snow quality prediction in northern Sweden. På grund av klimatförändringar och naturliga meteorologiska händelser i arktis behövs mer exakta snökvalitetsprognoser för att stödja samernas rensköttsamhällen i norra Sverige som har problem med att anpassa sig till det snabbt föränderliga arktiska klimatet. Rumslig snödjupsfördelning är en avgörande parameter för att inte bara bedöma snökvaliteten utan även för flera miljöforskning och sociala markanvändningsändamål. Detta står i motsats till den nuvarande tillgången till överkomliga och effektiva metoder för snöövervakning för att uppskatta sådan extremt varierande parameter i tid och rum. I detta arbete presenteras och testas en ny metod för att bestämma rumslig snödjupssdistribution i utmanande alpin terräng under en fältstudie som genomfördes i Tarfala i norra Sverige i april 2019. Via fotogrammetrisk bildbehandlingsteknik hämtades snöytemodeller i 3D med hjälp av en multispektral kamera monterad på en liten obemannad drönare. En viktig fördel, i jämförelse med konventionella fotogrammetriska undersökningar, är användningen av exakt RTK-positioneringsteknik som möjliggör direkt georeferencing och eliminerar behovet av markkontrollpunkter. Den kontinuerliga snödjupfördelningen hämtas genom att ytmodellerna delas upp i snöfria respektive snötäckta undersökningsområden. En omfattande felsökning som baseras på markmätningar utförs, inklusive en analys av effekten av multispektrala bilder. Resultaten från denna studie visar att den famtagna metoden kan producera högupplösta snötäckta höjdmodeller i 3D (< 7 cm/pixel) av alpina områden på upp till 8 hektar på ett snabbt, pålitligt och kostnadseffektivt sätt. Den övergripande RMSE för det beräknade snödjupet är 7,5 cm för data som förvärvats under idealiska undersökningsförhållanden. Som ett led i det svenska projektet “Snow4all” används resultaten från projektet för att förbättra och validera storskaliga snömodeller för att bättre förutse snökvaliteten i norra Sverige.

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Power, Sarah Nicole. "Microbial Mat Abundance and Activity in the McMurdo Dry Valleys, Antarctica." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/101078.

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Primary productivity is a fundamental ecological process and an important measure of ecosystem response to environmental change. Currently, there is a considerable lapse in our understanding of primary productivity in hot and cold deserts, due to the difficulty of measuring production in cryptogam vegetation. However, remote sensing can provide long-term, spatially-extensive estimates of primary production and are particularly well suited to remote environments, such as in the McMurdo Dry Valleys (MDV) of Antarctica, where cyanobacterial communities are the main drivers of primary production. These microbial communities form multi-layered sheets (i.e., microbial mats) on top of desert pavement. The cryptic nature of these communities, their often patchy spatial distribution, and their ability to survive desiccation make assessments of productivity challenging. I used field-based surveys of microbial mat biomass and pigment chemistry in conjunction with analyses of multispectral satellite data to examine the distribution and activity of microbial mats. This is the first satellite-derived estimate of microbial mat biomass for Antarctic microbial mat communities. I show strong correlations between multispectral satellite data (i.e., NDVI) and ground based measurements of microbial mats, including ground cover, biomass, and pigment chemistry. Elemental (C, N) and isotopic composition (15N, 13C) of microbial mats show that they have significant effects on biogeochemical cycling in the soil and sediment of this region where they occur. Using these relationships, I developed a statistical model that estimates biomass (kg of C) in selected wetlands in the Lake Fryxell Basin, Antarctica. Overall, this research demonstrates the importance of terrestrial microbial mats on C and N cycling in the McMurdo Dry Valleys, Antarctica. Master of Science

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Holm, Ovrén Hannes, and Erika Emilsson. "Missile approach warning using multi-spectral imagery." Thesis, Linköping University, Department of Electrical Engineering, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-57147.

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Man portable air defence systems, MANPADS, pose a big threat to civilian and military aircraft. This thesis aims to find methods that could be used in a missile approach warning system based on infrared cameras.The two main tasks of the completed system are to classify the type of missile, and also to estimate its position and velocity from a sequence of images.The classification is based on hidden Markov models, one-class classifiers, and multi-class classifiers.Position and velocity estimation uses a model of the observed intensity as a function of real intensity, image coordinates, distance and missile orientation. The estimation is made by an extended Kalman filter.We show that fast classification of missiles based on radiometric data and a hidden Markov model is possible and works well, although more data would be needed to verify the results.Estimating the position and velocity works fairly well if the initial parameters are known. Unfortunately, some of these parameters can not be computed using the available sensor data.

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Beckett, Kirsty A. "Multispectral analysis of high spatial resolution 256-channel radiometrics for soil and regolith mapping." Thesis, Curtin University, 2007. http://hdl.handle.net/20.500.11937/1434.

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Over the past decade studies into the application of radiometrics for soil and regolith mapping have met with mixed response. While the use of radiometric data for regolith mapping has been generally well received, radiometric methods have not commonly been adopted to assist and improve soil mapping. This thesis contributes to the development of radiometric techniques as soil and regolith mapping tools by examining soil characteristics and radiometric response using non-standard radiometric methods. This is accomplished through the development of new data processing methodologies, which extracts additional information from standard radiometric data that is unattainable using standard processing methods, and development of a new interpretation approach to soil and regolith mapping employing the multispectral processed radiometric data. The new multispectral processing methodology resolves seven gamma ray peaks from standard 256-channel NaI radiometric data to produce new radiometric uranium ternary, thorium ternary and uranium ratio imagery. Changes in the gamma ray relationships, identified through the new imagery, identify changes in soil and/or environmental conditions that are absent or difficult to identify in the standard radiometric imagery. With the isolation of non-standard thorium channels 228 [superscript] Ac (900 keV) and 228 [superscript] Ac (1600 keV), case studies in this thesis demonstrate how the difference of 1.9 years (half-life) between thorium 228 [superscript] Ac and 232 [superscript] Th decay daughter products can be mapped through the interpretation of thorium energy using ternary imagery [red: 208 [superscript] Tl (1764 keV), green: 228 [superscript] Ac (900 keV), blue: 228 [superscript] Ac (1600 keV)]. Energy peak differences may be be linked to local variations in soil chemistry, soil movement, and water movement.Additionally, through the isolation of non-standard uranium channels 214 [superscript] Bi (1120 keV) and 214 [superscript] Bi (1253 keV), preferential attenuation of lower energy gamma-rays from 214 [superscript] Bi decay events are exploited to map variations in soil density and/or porosity. These variations are illustrated through the interpretation of uranium energy using ternary imagery [red: 214 [superscript] Bi (1764 keV), green: 214 [superscript] Bi (1120 keV), blue: 214 [superscript] Bi (1253 keV)] and uranium peak energy ratio [214 [superscript] Bi 1120 keV / 214 [superscript] Bi 1764 keV] pseudo colour imagery. Case studies examined in this thesis explore the characteristics of 256-channel radiometric spectrum from different resolution datasets from different Western Australian soil types, provide recommendations for acquiring radiometric data for soil mapping in different agricultural environments, demonstrate how high resolution 256-channel radiometric data can be used to model soil properties in three-dimensions, and illustrate how three-dimension soil models can be used to separate surface waterlogging influences from rising groundwater induced waterlogging.

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Humphrey, Matthew Donald. "Texture analysis of high resolution panchromatic imagery for terrain classification." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03Jun%5FHumphrey.pdf.

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Beckett, Kirsty A. "Multispectral analysis of high spatial resolution 256-channel radiometrics for soil and regolith mapping." Curtin University of Technology, Dept. of Exploration Geophysics, 2007. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=17703.

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Over the past decade studies into the application of radiometrics for soil and regolith mapping have met with mixed response. While the use of radiometric data for regolith mapping has been generally well received, radiometric methods have not commonly been adopted to assist and improve soil mapping. This thesis contributes to the development of radiometric techniques as soil and regolith mapping tools by examining soil characteristics and radiometric response using non-standard radiometric methods. This is accomplished through the development of new data processing methodologies, which extracts additional information from standard radiometric data that is unattainable using standard processing methods, and development of a new interpretation approach to soil and regolith mapping employing the multispectral processed radiometric data. The new multispectral processing methodology resolves seven gamma ray peaks from standard 256-channel NaI radiometric data to produce new radiometric uranium ternary, thorium ternary and uranium ratio imagery. Changes in the gamma ray relationships, identified through the new imagery, identify changes in soil and/or environmental conditions that are absent or difficult to identify in the standard radiometric imagery. With the isolation of non-standard thorium channels 228 [superscript] Ac (900 keV) and 228 [superscript] Ac (1600 keV), case studies in this thesis demonstrate how the difference of 1.9 years (half-life) between thorium 228 [superscript] Ac and 232 [superscript] Th decay daughter products can be mapped through the interpretation of thorium energy using ternary imagery [red: 208 [superscript] Tl (1764 keV), green: 228 [superscript] Ac (900 keV), blue: 228 [superscript] Ac (1600 keV)]. Energy peak differences may be be linked to local variations in soil chemistry, soil movement, and water movement. Additionally, through the isolation of non-standard uranium channels 214 [superscript] Bi (1120 keV) and 214 [superscript] Bi (1253 keV), preferential attenuation of lower energy gamma-rays from 214 [superscript] Bi decay events are exploited to map variations in soil density and/or porosity. These variations are illustrated through the interpretation of uranium energy using ternary imagery [red: 214 [superscript] Bi (1764 keV), green: 214 [superscript] Bi (1120 keV), blue: 214 [superscript] Bi (1253 keV)] and uranium peak energy ratio [214 [superscript] Bi 1120 keV / 214 [superscript] Bi 1764 keV] pseudo colour imagery. Case studies examined in this thesis explore the characteristics of 256-channel radiometric spectrum from different resolution datasets from different Western Australian soil types, provide recommendations for acquiring radiometric data for soil mapping in different agricultural environments, demonstrate how high resolution 256-channel radiometric data can be used to model soil properties in three-dimensions, and illustrate how three-dimension soil models can be used to separate surface waterlogging influences from rising groundwater induced waterlogging.

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Bryant, Johnny. "The use of remotely sensed LiDAR and multispectral imagery for modeling eastern redcedar biomass within North Eastern Kansas." Thesis, Kansas State University, 2016. http://hdl.handle.net/2097/34622.

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Master of Arts Department of Geography Kevin P. Price Due in large part to changes in land management practices, eastern redcedar (Juniperus virginiana L.), a native Kansas conifer, is rapidly invading onto valuable rangelands. The suppression of fire and increase of intensive grazing, combined with the rapid growth rate, high reproductive output, and dispersal ability of the species have allowed it to dramatically expand beyond its original range. Based on its abundance and invasive nature there is a growing interest in harvesting this species for use as a biofuel. For economic planning purposes, density and biomass quantities for the trees are needed. Three methods are explored for mapping eastern redcedar and quantifying its biomass in Riley County, Kansas. First a comparison of plot-regression versus individual tree based techniques is conducted to determine the optimal approach for characterizing redcedar tree canopy using LiDAR (Light Detection and Ranging). Second a hybrid approach is utilized to characterize redcedar canopy biomass using LiDAR and high-resolution multispectral imagery. Finally, to explore alternative methods of characterizing the three-dimensional structure of redcedar canopy a comparison of “Structure from Motion” photogrammetric techniques and LiDAR is conducted. These methods showed promising results and proved to be useful in the forestry, range management, and bioenergy industries for better understanding the potential of invasive redcedar as a biofuel resource.

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Gallie, Elizabeth Ann. "Chromaticity analysis of LANDSAT Multispectral Scanner and Thematic Mapper imagery of Chilko Lake, British Columbia, using a theoretical optical water quality model." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/30572.

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Chromaticity analysis of LANDSAT Multispectral Scanner (MSS) imagery of Chilko Lake, B.C. reveals a. locus whose shape has not been previously reported. To investigate the cause of this and to come to a broader understanding of chromaticity analysis for MSS and Thematic Mapper (TM) data, an optical water quality model has been used. The model is composed of a four component reflectance model (R-model), an interface model and an atmospheric model. The R-model was calibrated for Chilko Lake by determining the specific absorption and backscattering spectra for suspended minerals (SM), chlorophyll-a uncorrected for phaeophytins (C) and yellow substance (YS). The fourth component is water. The model reproduces the observed locus shape and indicates that it is primarily a function of SM, with the unreported lower limb on MSS imagery caused by SM gradients with concentrations less than 1-2 mg/L. The effects of C, YS and SM cannot be separated on plots of chromaticity coordinates X and Y for either MSS or TM data. In addition, haze or wind gradients, if they occur over water with low levels of SM, would look similar to the lower limb on MSS XY plots. However, if brightness is used in combination with X, the model predicts that C and YS, though themselves inseparable, can be differentiated from SM at all but the lowest concentrations of SM. Furthermore, haze and wind gradients can be distinguished from the lower limb. Thus the addition of brightness to chromaticity analysis has the potential to significantly improve the technique. The model was tested by comparing simulated chromaticity results with results from actual images (one TM image and three MSS images) for which ground truth had been collected. Qualitative predictions regarding haze and water quality patchiness were confirmed. Correlation analysis with R² values from 0.81 to 0.95 also strongly confirmed predictions regarding SM, but showed that the model is systematically underestimating SM. Correlation tests for a combined C and YS factor (CYS) were inconclusive because of the systematic modeling error, but classification maps provide weak evidence that CYS is behaving qualitatively as predicted and that CYS can be differentiated from SM. The modeling error is thought to originate in atmospheric assumptions which are not met. The R-model which is fundamental to the study has been tested and is not a major source of error. The study concludes that the model is qualitatively correct and that the use of brightness improves chromaticity analysis by allowing separation of CYS and SM, though further work should be undertaken to verify these results. Maps of CYS and SM in Chilko Lake reveal that CYS tends to be higher along the western shore and where the hypolimnion is exposed. SM are highest near stream mouths. The distribution patterns are related to physical processes within the lake and provide a synoptic view of the connection between water quality parameters and circulation which would be difficult to achieve in any other way. Forestry, Faculty of Graduate

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Farineau, Anne. "Diamonds in the Rough : Remote predictive mapping using multispectral satellite imagery for kimberlite exploration on northeast Banks Island, NT." Thesis, Stockholms universitet, Institutionen för naturgeografi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-125966.

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This study demonstrates the use and limitations of Remote Predictive Mapping (RPM) as an aid to kimberlite exploration on northeast Banks Island, Northwest Territories, Canada. It focuses on the effectiveness of ASTER and Landsat 8 optical multi-spectral satellite imagery for discerning the spectral properties of different bedrock and surficial materials that outcrop or blanket the regional terrain. Statistical algorithms and digital image enhancement techniques were used to highlight patterns and anomalies within each scene in order to determine the range of materials and specific deposits (e.g., till, glaciofluvial) that could be the source of recovered kimberlite indicator minerals (KIMs) from stream sediment samples. Field inspection and sampling were in part guided by these patterns and anomalies. During the course of fieldwork, numerous outliers of the Pliocene Beaufort Formation fluvial sand and gravel deposits were discovered on upland surfaces in northeastern Banks Island. These outcrops sit well beyond (east) of any previous mapped Beaufort Fm. extents, and it is hypothesized that as they exist within catchments where Industry has recovered KIMs, they could be a source of bedrock-inherited KIMs. Field observations and spectral sampling using a portable spectroradiometer were integrated with ASTER and Landsat data to predict the spatial extents of Beaufort Fm. deposits. Using test and field-validated Beaufort Fm. sites, Spectral Angle Mapper (SAM) whole pixel spectral target detection was compared with Matched Filtering (MF), Mixture-Tuned Matched Filtering (MTMF) sub-pixel spectral target detection methods and Parallelepiped classification for ASTER scenes 1228 and 0686. Each method was also performed on ASTER scene 0541 to assess the potential for Quaternary sediment discrimination, using pixel ROIs from a field-validated glaciolacustrine deposit. The sub-pixel sensitivity of the MF/MTMF methods was determined to have the best potential for the discrimination of surficial materials on NE Banks Island. MF/MTMF also had the best results for discriminating Beaufort Fm. in scene 1228, but Parallelepiped classification was the most effective prediction method for scene 0686. These inconsistent results indicate spectral variability between Beaufort Fm. sites, a consideration for any further study in the region.

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Repaka, Sunil Reddy. "Comparing spectral-object based approaches for extracting and classifying transportation features using high resolution multi-spectral satellite imagery." Master's thesis, Mississippi State : Mississippi State University, 2004. http://library.msstate.edu/etd/show.asp?etd=etd-11082004-231712.

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Khan, Haris Ahmad. "Multispectral constancy for illuminant invariant representation of multispectral images." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCK028/document.

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En imagerie couleur, un système d’acquisition capture une scène avec une haute résolution spatiale mais une résolution spectrale limitée. L’imagerie hyperspectrale permet d’acquérir la scène avec une grande résolution spectrale. Un système d’acquisition hyperspectrale est un ensemble complexe et il est difficile de l’utiliser pour acquérir des données dans une situation où les conditions d’imageries ne sont pas contrôlées. De plus, ces systèmes sont chers et souvent encombrants ou difficiles à manipuler. À cause de ces problèmes, l’utilisation de l’imagerie hyperspectrale n’a pas encore été beaucoup utilisée en vision assistée par ordinateur, et la plupart des systèmes de vision utilise l’imagerie couleur.L’imagerie multispectrale propose une solution intermédiaire, elle permet de capturer une information moins résolue selon la dimension spectrale, comparée à l’hyperspectrale, tout en préservant la résolution spatiale. Ces systèmes sont moins encombrants et moins difficiles à maitriser grâce aux récentes avancées technologiques, et arrivent sur le marché en tant que produits commerciaux. On peut citer les matrices de filtres spectraux (spectral filter arrays) qui permettent l’acquisition en temps réel d’images multispectrales grâce à l’utilisation d’unecaméra de complexité similaire à une caméra couleur. Jusqu’ici, les informations capturées par ces systèmes étaient considérées de la même manière que les imageurs hyperspectraux en champ proche, c’est à dire que pour utiliser l’information au mieux, les conditions d’acquisitions devaient être connues et le système calibré, en particulier pour l’éclairage de la scène et la dynamique de la scène.Afin d’élargir l’utilisation de l’imagerie multispectrale pour la vision par ordinateur dans des conditions générales, je propose dans cette thèse de développer les méthodes calculatoires en imagerie couleur (computational color imaging) et de les adapter aux systèmes d’imagerie multispectraux. Une caractéristique très puissante de l’imagerie couleur est de proposer un rendu constant des couleurs de la surface d’un objet à travers différentes conditions d’acquisition via l’utilisation d’algorithmes et divers traitements de l’information.Dans cette thèse, j’étends la notion de constance des couleurs et de balance des blancs de l’imagerie couleur à l’imagerie multispectrale. J’introduis le terme de constance de l’information spectrale (multispectral constancy).Je propose la construction d’un ensemble d’outils permettant la représentation constante de l’information spectrale à travers le changement d’éclairage. La validité de ces outils est évaluée à travers la reconstruction de la réflectance spectrale des objets lorsque l’éclairage change. Nous avons également acquis de nouvelles images hyperspectrales et multispectrales mises à disposition de la communauté.Ces outils et données permettront de favoriser la généralisation de l’utilisation de l’imagerie multispectrale en champ proche dans les applications classiques utilisant traditionnellement l’imagerie couleur et de sortir ce mode d’imagerie des laboratoires. L’avantage en vision par ordinateur est une meilleure analyse de la réflectance de la surface des objets et donc un avantage certain dans les tâches de classification et d’identification de matériaux A conventional color imaging system provides high resolution spatial information and low resolution spectral data. In contrast, a multispectral imaging system is able to provide both the spectral and spatial information of a scene in high resolution. A multispectral imaging system is complex and it is not easy to use it as a hand held device for acquisition of data in uncontrolled conditions. The use of multispectral imaging for computer vision applications has started recently but is not very efficient due to these limitations. Therefore, most of the computer vision systems still rely on traditional color imaging and the potential of multispectral imaging for these applications has yet to be explored.With the advancement in sensor technology, hand held multispectral imaging systems are coming in market. One such example is the snapshot multispectral filter array camera. So far, data acquisition from multispectral imaging systems require specific imaging conditions and their use is limited to a few applications including remote sensing and indoor systems. Knowledge of scene illumination during multispectral image acquisition is one of the important conditions. In color imaging, computational color constancy deals with this condition while the lack of such a framework for multispectral imaging is one of the major limitation in enabling the use of multispectral cameras in uncontrolled imaging environments.In this work, we extend some methods of computational color imaging and apply them to the multispectral imaging systems. A major advantage of color imaging is the ability of providing consistent color of objects and surfaces across varying imaging conditions. In this work, we extend the concept of color constancy and white balancing from color to multispectral images, and introduce the term multispectral constancy.The validity of proposed framework for consistent representation of multispectral images is demonstrated through spectral reconstruction of material surfaces from the acquired images. We have also presented a new hyperspectral reflectance images dataset in this work. The framework of multispectral constancy will make it one step closer for the use of multispectral imaging in computer vision applications, where the spectral information, as well as the spatial information of a surface will be able to provide distinctive useful features for material identification and classification tasks

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Benmoussat, Mohammed Seghir. "Hyperspectral imagery algorithms for the processing of multimodal data : application for metal surface inspection in an industrial context by means of multispectral imagery, infrared thermography and stripe projection techniques." Thesis, Aix-Marseille, 2013. http://www.theses.fr/2013AIXM4347/document.

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Le travail présenté dans cette thèse porte sur l'inspection de surfaces métalliques industrielles. Nous proposons de généraliser des méthodes de l'imagerie hyperspectrale à des données multimodales comme des images optiques multi-canales, et des images thermographiques multi-temporelles. Dans la première application, les cubes de données sont construits à partir d'images multi-composantes pour détecter des défauts de surface. Les meilleures performances sont obtenues avec les éclairages multi-longueurs d'ondes dans le visible et le proche IR, et la détection du défaut en utilisant l'angle spectral, avec le spectre moyen comme référence. La deuxième application concerne l'utilisation de l'imagerie thermique pour l'inspection de pièces métalliques nucléaires afin de détecter des défauts de surface et sub-surface. Une approche 1D est proposée, basée sur l'utilisation du kurtosis pour sélectionner la composante principale parmi les premières obtenues après réduction des données avec l’ACP. La méthode proposée donne de bonnes performances avec des données non-bruitées et homogènes, cependant la SVD avec les algorithmes de détection d'anomalies est très robuste aux perturbations. Finalement, une approche, basée sur les techniques d'analyse de franges et la lumière structurée est présentée, dans le but d'inspecter des surfaces métalliques à forme libre. Après avoir déterminé les paramètres décrivant les modèles de franges sinusoïdaux, l'approche proposée consiste à projeter une liste de motifs déphasés et à calculer l'image de phase des motifs enregistrés. La localisation des défauts est basée sur la détection et l'analyse des franges dans les images de phase The work presented in this thesis deals with the quality control and inspection of industrial metallic surfaces. The purpose is the generalization and application of hyperspectral imagery methods for multimodal data such as multi-channel optical images and multi-temporal thermographic images. In the first application, data cubes are built from multi-component images to detect surface defects within flat metallic parts. The best performances are obtained with multi-wavelength illuminations in the visible and near infrared ranges, and detection using spectral angle mapper with mean spectrum as a reference. The second application turns on the use of thermography imaging for the inspection of nuclear metal components to detect surface and subsurface defects. A 1D approach is proposed based on using the kurtosis to select 1 principal component (PC) from the first PCs obtained after reducing the original data cube with the principal component analysis (PCA) algorithm. The proposed PCA-1PC method gives good performances with non-noisy and homogeneous data, and SVD with anomaly detection algorithms gives the most consistent results and is quite robust to perturbations such as inhomogeneous background. Finally, an approach based on fringe analysis and structured light techniques in case of deflectometric recordings is presented for the inspection of free-form metal surfaces. After determining the parameters describing the sinusoidal stripe patterns, the proposed approach consists in projecting a list of phase-shifted patterns and calculating the corresponding phase-images. Defect location is based on detecting and analyzing the stripes within the phase-images

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Wilson, Natalie R. "A Comparison of Remote Sensing Indices and a Temporal Study of Cienegas at Cienega Creek from 1984 to 2011 using Multispectral Satellite Imagery." The University of Arizona, 2014. http://hdl.handle.net/10150/337200.

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Desert wetlands, in particular those slow moving bodies of water known as cienegas, are important sites for biodiversity in arid landscapes and serve as indicators of hydrological functioning on the landscape-level. One of the most extensive systems of cienegas, historical or extant, in southeastern Arizona lies along Cienega Creek, located southeast of Tucson, Arizona. Satellite imagery analysis is heavily utilized to determine landscape-level trends, but cienegas present a challenge to traditional analysis methods. The Normalized Difference Vegetation Index (NDVI), the classic measure of vegetation greenness, reacts counter-intuitively to open water and is affected by open ground, both common occurrences in cienega habitats. Additional remote sensing indices have been developed that balance sensitivity to these environmental elements. This research explores these remote sensing indices at Cienega Creek applying one topographic index to current elevation data and five spectral indices to Thematic Mapper imagery from 1984 to 2011. Temporal trends were identified for all spectral indices and all indices were compared for suitability in cienega habitats. Temporal trends were analyzed for spatial clustering and spatial trends identified. The Normalized Difference Infrared Index utilizing Landsat Thematic Mapper band 5 outperformed other indices at differentiating between cienega, riparian, and upland habitats and is more suitable than NDVI for analyzing cienega habitats in such circumstances.

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Julius, Alexandria Marie. "Characterizing Disaster Resilience Using Very High Resolution Time-Sequence Stereo Imagery." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524211742718203.

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Pritsolas, Joshua. "Principal Component Analysis and Spatial Regression Techniques to Model and Map Corn and Soybean Yield Variability with Radiometrically Calibrated Multitemporal and Multispectral Digital Aerial Imagery." Thesis, Southern Illinois University at Edwardsville, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10807753.

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Remotely sensed data has been discussed as a possible alternative to the standard precision agriculture systems of combine-mounted yield monitors because of the burden, cost, end of season use, and inherent errors that are associated with these systems. Due to the potential quantitative use of remote sensing in precision agriculture, the primary focus of this study was to test the relationship between multitemporal/multispectral digital aerial imagery with corn (Zea mays L.) and soybean (Glycine max L.) yield. Digital aerial imagery was gathered on nine different dates throughout the 2015 growing season from two fields (one corn and one soybean) located on a farm in Story County, Iowa. To begin assessing this relationship, the digital aerial imagery was radiometrically calibrated. The radiometric calibration process used calibration tarps with known reflectance values (3, 6, 12, 22, 44, and 56 percent). The calibrated imagery was then used to calculate and output 12 different vegetation indices (VIs) and three calibrated wavebands (red, green, and near-infrared). Next, the calibrated VIs and wavebands from the 2015 growing season were used to examine their relationship with the corn and soybean yield data collected from a combine yield monitor system. This relationship between multitemporal/multispectral digital aerial imagery with corn and soybean yield was investigated with principal component analysis and spatial modeling techniques. The results from spatial modeling of corn revealed that VIs utilizing the green waveband performed strongly. VIs such as, chlorophyll index-green, chlorophyll vegetation index, and green normalized difference vegetation index accounted for 81.6, 83.0, and 82.4 percent of the yield variability, respectively. Strong modeling relationships were also found in soybean using just the near-infrared waveband or VIs that utilized the near-infrared waveband. The near-infrared waveband captured 89.1 percent of the yield variation, while VIs such as, difference vegetation index, triangular vegetation index, soil adjusted vegetation index, and optimized soil adjusted vegetation index accounted for 87.3, 87.3, 83.9, and 83.8 percent of soybean yield variability, respectively. The temporal assessment of the remotely sensed data also identified certain VIs and wavebands that captured pivotal growth stages for detecting potential yield limiting factors. These specific growth stages varied for different VIs and wavebands for both corn and soybean. Overall, the results from this study identified that mid-to-late vegetative growth stages (prior to tasseling) and late-season reproductive stages were important parameters that provided unique information in the modeling of corn yield variability, while the later reproductive stages (just prior to senescence) were essential to capturing soybean yield variability. Lastly, this research produced corn and soybean yield maps from the digital aerial imagery. The digital aerial imagery yield maps were then compared with maps that used kriging interpolation of the combine yield monitor data gathered from the same corn and soybean fields. The results indicated that both corn and soybean yield maps produced with multitemporal/multispectral digital aerial imagery were comparable with a standard method of kriging interpolation from yield monitor data.

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Meng, Goh Chuan. "Estimation de profondeur de veine sous-invasive non invasive utilisant une imagerie multispectrale et des images de réflectance diffuses." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCK081.

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L'estimation de la profondeur des veines sous-cutanées a été un sujet de recherche important ces dernières années en raison de son importance dans l'optimisation de pose de cathéters, de perfusions et plus généralement de ponctions veineuses. Par le passé, diverses techniques et systèmes de visualisation des veines ont été proposés, cependant le manque d'information sur la profondeur de la veine limite les possibilités pour une automatisation de la ponction veineuse ; le geste clinique restant dans de nombreux cas tributaire des compétences ou de l'expérience des cliniciens. Plusieurs techniques ont été proposées pour estimer la profondeur de la veine en utilisant la réflectance diffuse dont le principe repose sur la mesure de rapport de densité optique (ODR). Le concept de mesure de la profondeur des veines à l'aide de la technique ODR mérite d'être appliqué dans le monde réel en raison de son faible coût, de ses propriétés non invasives et du fait qu'il s'agit d'une technique de mesure sans contact avec la peau. Les travaux initiaux de Nishidate et. Al. [1] ont montré sur fantôme des résultats prometteurs. Cependant, une telle expérience peut ne pas être suffisante pour prouver son application pour la mesure in vivo en raison du manque d'expérience pour les données réelles. Par conséquent, ce travail de thèse a été commencé pour améliorer le modèle proposé par Nishidate et. Al. et l'élargir pour mesurer l'estimation in vivo de la profondeur de la veine sur de vrais patients. Le système proposé intègre de nouveaux composants tels qu'un algorithme de segmentation des veines, une méthode d'estimation plus précise du contenu en mélanine (Cm) et une conception matérielle entièrement nouvelle avec des composants stables. Les résultats obtenus par ODR ont été comparés à des données fournies par une machine Ultrason médicale. Les résultats de l'expérience montrent une corrélation de Pearson forte de 0,843 par rapport aux données échographiques et prouvent que le système développé est fiable pour la mesure in vivo de la profondeur de la veine. En outre, il est proposé d'utiliser un filtre de segmentation de veine optimal (filtre adapté) dans le système d'imagerie pour permettre une segmentation et par la suite une mesure de la profondeur automatique The estimation of subcutaneous vein depth has been an important research topic in recent years due to its importance in optimizing the intravenous (IV) access of venipuncture. Various techniques and system of vein visualization were proposed to improve the vein viewing, but the lack of vein depth information limits the system performance in assisting the IV access; thus, the IV access in many cases remains dependent on skill or experience of the clinicians. Several techniques were proposed to estimate the vein depth using diffuse reflectance of which the optical density ratio (ODR) technique is the most complete solution. The concept of measuring the veins depth using ODR based technique is deserved to be applied in the real-world due to its low cost, non-invasive properties and from the fact that it is a non-skin contact measurement technique. Nishidate et. al. [1] suggested an optimum conditions to measure the vein depth and thickness by using ODR which was supported by experiment with customized tissue-like agar gel phantom. However, such experiment may not be sufficient to prove its application for in vivo measurement due to the lack of experiment for real data. Therefore, this thesis work was first started to improve the proposed model by Nishidate et. al. and expand it to measure the in vivo estimation of vein depth on real patients. The proposed system incorporates new components such as an autonomous vein segmentation algorithm, a more accurate estimation method for melanin content (Cm) and a fully new hardware design with reliable parts. Importantly, the experiment estimate the vein depth on real patients as well as a through comparison with Ultrasound data. The experiment results show a strong Pearson correlation of 0.843 as compared to Ultrasound data and this evidence that the developed system is works for the in vivo measurement of vein depth. Besides that, an optimum vein filter (matched filter) is proposed to be used in the imaging system to preserve the most accurate vein detection and allow the system to produce the results with least detection error. The selection of the optimum vein filter has laid an important platform from which to obtain the accurate vein segmentation of a NIR image

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Rhoul, Camill. "Simulation de la fluorescence de la végétation mesurée depuis une orbite géostationnaire." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLX097/document.

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Le travail de cette thèse porte sur l’étude de la télédétection de la fluorescence chlorophyllienne avec un instrument imageur passif depuis une orbite géostationnaire pour le suivi de l’état physiologique de la végétation. Le concept instrumental est étudié théoriquement pour aboutir à la création d’uninstrument et à sa validation. La possibilité de mesurer des cycles diurnes de la fluorescence végétale depuis une orbite géostationnaire est évaluée à l’aide de simulations qui permettent de dresser les spécifications d’un instrument spatial.L’instrument imageur passif mesure dans la bande O 2 -A d’absorption atmosphérique. Il utilise une roue à filtres interférentiels dont la fonction de transmittance varie avec l’angle d’incidence des rayons les traversant. L’étude théorique a permis d’optimiser le placement spectral des filtres en vuede minimiser l’incertitude liée à la mesure de fluorescence.Grâce à la comparaison des mesures de l’instrument imageur avec d’autres instrument de mesure de la fluorescence, l’instrument et son concept instrumental ont été validés. Néanmoins, à cause d’effets de structure de la végétation intervenant sur le transfert radiatif de la fluorescence et de la lumière solaire au sein du couvert végétal, ces mesures ont confirmé la difficulté d’estimer le rendement de fluorescence de la végétation à partir des flux de fluorescence mesurés.Une étude théorique menée grâce à une modélisation du transfert radiatif de la fluorescence dans le couvert végétal jusqu’au capteur a permis d’expliquer la difficulté à retrouver le rendement de fluorescence à partir des flux. Cette étude a mis en avant l’accessibilité du rendement pour des couverts à fortedensité de feuilles et lorsque la distribution de l’orientation des feuilles est centrée sur l’horizontale.Cette modélisation a été étendue pour simuler des mesures spatiales dans le but d’étudier la possibilité de mesurer la fluorescence depuis une orbite géostationnaire dans les bandes O 2 -A et O 2 -B. Les résultats de ces simulations montrent la possibilité de mesurer préférentiellement dans la bandeO 2 -A avec une faible incertitude sur les flux de fluorescence et une bonne répétabilité temporelle pour le suivi des cycles diurnes de la fluorescence de la végétation Le travail de cette thèse porte sur l’étude de la télédétection de la fluorescence chlorophyllienne avec un instrument imageur passif depuis une orbite géostationnaire pour le suivi de l’état physiologique de la végétation. Le concept instrumental est étudié théoriquement pour aboutir à la création d’uninstrument et à sa validation. La possibilité de mesurer des cycles diurnes de la fluorescence végétale depuis une orbite géostationnaire est évaluée à l’aide de simulations qui permettent de dresser les spécifications d’un instrument spatial.L’instrument imageur passif mesure dans la bande O 2 -A d’absorption atmosphérique. Il utilise une roue à filtres interférentiels dont la fonction de transmittance varie avec l’angle d’incidence des rayons les traversant. L’étude théorique a permis d’optimiser le placement spectral des filtres en vuede minimiser l’incertitude liée à la mesure de fluorescence.Grâce à la comparaison des mesures de l’instrument imageur avec d’autres instrument de mesure de la fluorescence, l’instrument et son concept instrumental ont été validés. Néanmoins, à cause d’effets de structure de la végétation intervenant sur le transfert radiatif de la fluorescence et de la lumière solaire au sein du couvert végétal, ces mesures ont confirmé la difficulté d’estimer le rendement de fluorescence de la végétation à partir des flux de fluorescence mesurés.Une étude théorique menée grâce à une modélisation du transfert radiatif de la fluorescence dans le couvert végétal jusqu’au capteur a permis d’expliquer la difficulté à retrouver le rendement de fluorescence à partir des flux. Cette étude a mis en avant l’accessibilité du rendement pour des couverts à fortedensité de feuilles et lorsque la distribution de l’orientation des feuilles est centrée sur l’horizontale.Cette modélisation a été étendue pour simuler des mesures spatiales dans le but d’étudier la possibilité de mesurer la fluorescence depuis une orbite géostationnaire dans les bandes O 2 -A et O 2 -B. Les résultats de ces simulations montrent la possibilité de mesurer préférentiellement dans la bandeO 2 -A avec une faible incertitude sur les flux de fluorescence et une bonne répétabilité temporelle pour le suivi des cycles diurnes de la fluorescence de la végétation

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Vallentin, Claudia [Verfasser], Birgit [Akademischer Betreuer] Kleinschmit, Birgit [Gutachter] Kleinschmit, Hermann [Gutachter] Kaufmann, and Christopher [Gutachter] Conrad. "Remote sensing for precision agriculture : yield mapping and delineation of management zones with multispectral satellite imagery and GIS data / Claudia Vallentin ; Gutachter: Birgit Kleinschmit, Hermann Kaufmann, Christopher Conrad ; Betreuer: Birgit Kleinschmit." Berlin : Technische Universität Berlin, 2021. http://d-nb.info/122843199X/34.

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Rhoul, Camill. "Simulation de la fluorescence de la végétation mesurée depuis une orbite géostationnaire." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLX097.

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Le travail de cette thèse porte sur l’étude de la télédétection de la fluorescence chlorophyllienne avec un instrument imageur passif depuis une orbite géostationnaire pour le suivi de l’état physiologique de la végétation. Le concept instrumental est étudié théoriquement pour aboutir à la création d’uninstrument et à sa validation. La possibilité de mesurer des cycles diurnes de la fluorescence végétale depuis une orbite géostationnaire est évaluée à l’aide de simulations qui permettent de dresser les spécifications d’un instrument spatial.L’instrument imageur passif mesure dans la bande O 2 -A d’absorption atmosphérique. Il utilise une roue à filtres interférentiels dont la fonction de transmittance varie avec l’angle d’incidence des rayons les traversant. L’étude théorique a permis d’optimiser le placement spectral des filtres en vuede minimiser l’incertitude liée à la mesure de fluorescence.Grâce à la comparaison des mesures de l’instrument imageur avec d’autres instrument de mesure de la fluorescence, l’instrument et son concept instrumental ont été validés. Néanmoins, à cause d’effets de structure de la végétation intervenant sur le transfert radiatif de la fluorescence et de la lumière solaire au sein du couvert végétal, ces mesures ont confirmé la difficulté d’estimer le rendement de fluorescence de la végétation à partir des flux de fluorescence mesurés.Une étude théorique menée grâce à une modélisation du transfert radiatif de la fluorescence dans le couvert végétal jusqu’au capteur a permis d’expliquer la difficulté à retrouver le rendement de fluorescence à partir des flux. Cette étude a mis en avant l’accessibilité du rendement pour des couverts à fortedensité de feuilles et lorsque la distribution de l’orientation des feuilles est centrée sur l’horizontale.Cette modélisation a été étendue pour simuler des mesures spatiales dans le but d’étudier la possibilité de mesurer la fluorescence depuis une orbite géostationnaire dans les bandes O 2 -A et O 2 -B. Les résultats de ces simulations montrent la possibilité de mesurer préférentiellement dans la bandeO 2 -A avec une faible incertitude sur les flux de fluorescence et une bonne répétabilité temporelle pour le suivi des cycles diurnes de la fluorescence de la végétation Le travail de cette thèse porte sur l’étude de la télédétection de la fluorescence chlorophyllienne avec un instrument imageur passif depuis une orbite géostationnaire pour le suivi de l’état physiologique de la végétation. Le concept instrumental est étudié théoriquement pour aboutir à la création d’uninstrument et à sa validation. La possibilité de mesurer des cycles diurnes de la fluorescence végétale depuis une orbite géostationnaire est évaluée à l’aide de simulations qui permettent de dresser les spécifications d’un instrument spatial.L’instrument imageur passif mesure dans la bande O 2 -A d’absorption atmosphérique. Il utilise une roue à filtres interférentiels dont la fonction de transmittance varie avec l’angle d’incidence des rayons les traversant. L’étude théorique a permis d’optimiser le placement spectral des filtres en vuede minimiser l’incertitude liée à la mesure de fluorescence.Grâce à la comparaison des mesures de l’instrument imageur avec d’autres instrument de mesure de la fluorescence, l’instrument et son concept instrumental ont été validés. Néanmoins, à cause d’effets de structure de la végétation intervenant sur le transfert radiatif de la fluorescence et de la lumière solaire au sein du couvert végétal, ces mesures ont confirmé la difficulté d’estimer le rendement de fluorescence de la végétation à partir des flux de fluorescence mesurés.Une étude théorique menée grâce à une modélisation du transfert radiatif de la fluorescence dans le couvert végétal jusqu’au capteur a permis d’expliquer la difficulté à retrouver le rendement de fluorescence à partir des flux. Cette étude a mis en avant l’accessibilité du rendement pour des couverts à fortedensité de feuilles et lorsque la distribution de l’orientation des feuilles est centrée sur l’horizontale.Cette modélisation a été étendue pour simuler des mesures spatiales dans le but d’étudier la possibilité de mesurer la fluorescence depuis une orbite géostationnaire dans les bandes O 2 -A et O 2 -B. Les résultats de ces simulations montrent la possibilité de mesurer préférentiellement dans la bandeO 2 -A avec une faible incertitude sur les flux de fluorescence et une bonne répétabilité temporelle pour le suivi des cycles diurnes de la fluorescence de la végétation

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Larson, Matthew David. "Monitoring Multi-Depth Suspended Sediment Loads in Lake Erie's Maumee River using Landsat 8 and Unmanned Aerial Vehicle (UAV) Imagery." Bowling Green State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1496484122311721.

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Pronti, Lucilla. "Multispectral imaging of painting : potentialities and limitations of the technique in relation with the chemical and optical proprierties of the pictorial materials." Thesis, Avignon, 2016. http://www.theses.fr/2016AVIG0262/document.

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Cette thèse porte sur l’application des images multispectrales pour l’analyse des matériaux utilisés dans une peinture par comparaison avec la photographie traditionnelle de fluorescence induite par rayons UV et la réflectoraphgie infrarouge. L’application des images multispectrales à l'étude des matériaux picturaux a été appuyée par d'autres techniques analytiques telles que la spectroscopie de réflectance et de fluorescence, la spectroscopie de fluorescence X, la spectroscopie d'absorption UV-visible et la spectroscopie infrarouge transformée de Fourier en réflectance totale atténuée. L’imagerie multispectrale a été testée comme outil de laboratoire d’identification des matériaux picturaux. Ainsi, des couches de peinture constituées de pigments (anciens et modernes), de liants (œufs et l’huile de lin) et de vernis naturels ont été analysées. Pour les matériaux organiques, des expériences de vieillissement accéléré (photodégradation et dégradation thermique) ont permis de modéliser les changements optiques et chimiques intervenant au cours de la vie d’un tableau. De plus, une analyse diagnostique a été réalisée sur deux tableaux conservés à « Accademia di San Luca » (Rome) par photographie de fluorescence induite par rayonnement UV, radiographie, spectroscopie de réflectance, spectroscopie de fluorescence X, images de fluorescence UV et réflectance multispectrale, réflectographie infrarouge multispectrale. Par rapport aux techniques traditionnelles, les images multispectrales permettent d’analyser de nombreuses régions spectrales qui, dans certains cas, permettent d’identifier le pigment et/ou des zones non homogènes de la couche superficielle picturale. Certaines gammes de longueurs d’onde infrarouge permettent notamment de voir les détails des différentes couches préparatoires, amenant à une analyse plus précise de la technique d’exécution. Cependant, une des limites des images multispectrales concerne l’identification des mélanges complexes et/ou des différentes strates de matériaux en fonction du type de filtre utilisé This thesis focus on the application of multispectral images for the analysis of pictorial materials in comparison with the traditional UV-fluorescence photography and infrared reflectography. The assessment of multispectral imaging for the study of pictorial materials was supported by other analytical techniques such as reflectance and fluorescence spectroscopy, X-Ray Fluorescence (XRF), UV-visible absorption spectroscopy and Total Attenuated Reflectance - Fourier Transform Infrared Spectroscopy (ATR-FTIR). The multispectral imaging was tested on swatches of pictorial layers (constituted by ancient and modern pigment), binders (egg and linseed oil) and natural varnishes. For the organic materials, accelerated ageing methods (photo-chemical and thermal degradation) were used to model the optical and chemical changes occurring during the lifetime of a painting. In addition, a diagnostic investigation was performed on two paintings placed in "Accademia di San Luca" (Rome) by means of UV-fluorescence photography, radiography, reflectance spectroscopy, X-ray fluorescence spectroscopy, UV-VIS-NIR multispectral imaging. Multispectral images, comparing to traditional techniques, permit to individuate specific spectral behaviors, and, in some cases, identify the pigment and/or non-homogeneous areas of the pictorial or varnish layers. The possibility to select some infrared wavelengths allows to see details of the preparatory layers, leading to a more accurate analysis of the technique of execution. However, the limitations of multispectral images for the identification of complex mixtures and/or different layers of materials depending on the type of filter used

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Bardinet, Claude. "Teledetection, environnement et urbanisation : de l'image globale aux objets geographiques, applications a l'impact de l'urbanisation sur les paysages en afrique et en chine." Paris 8, 1987. http://www.theses.fr/1988PA080220.

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Les images numeriques de satellites nous donnent une vision nouvelle multispectrale et multitemporelle des paysages, a differentes echelles. On observe par satellites la signature spectrale des objets geographiques, c'est-a-dire la mesure du spectre d'un objet dans une ou plusieurs bandes (lumiere visible, infrarouge proche, moyen et thermique, bandes radar). Ce spectre est observe a differentes echelles en fonction du pixel (limite de resolution au sol). La recherche est axee sur l'afrique du nord, le sahel et l'afrique centrale, l'afrique de l'est et la chine de l'est. L'infographie de l'environnement est realisee a diverses echelles a partir d'une base de donnees multisatellites constituee lors de la realisation des programmes lanchad, simulation spot et codata. A echelle zonale, on cartographie par meteosat, l'algerie du nord, la regionale, on cartographie les paysages physiques de bandiagara et de mopti (mali) par meteosat, landsat mss et le radar sir-a; puis les paysages d'iringa et de karema (tanzanie) par meteosat, noaa-tiros n, landsat mss et tm; on cartographie la mise en valeur du milieu, soit la riziculture de mopti (mali) par simulation spot, des perimetres irrigues (djebel amour, algerie) par spot, l'emprise de l'amenagement hydro-agricole a xintai (hebei, chine de l'est) par landsat. Aux echelles urbaines, on cartographie la morphologie urbaine de n'djamena (tchad) et annaba (algerie) par landsat mss et par photographies aeriennes numerisees. On realise le pretraitement automatique des donnees par detection des contours et lineaments, puis la classification thematique dirigee. La realite de terrain a ete observee en algerie, au tchad, au mali, en tanzanie et en chine. On cherche a demontrer l'efficacite du traitement infographique des donnees satellitaires pour une cartographie de l'environnement Satellite's digital imagery gives us a new multispectral and multitemporal vision of landscapes at different scales. We observe the multispectral signature of geographical objects, that means quantitative measure of their properties at one or several wavelength intervals from visible to infrared (near, medium and thermal) and in radar bands. At each scale, the pixel gives the ground resolution and an integrated radiance mapping unit. The research is focused on north, central, sahelian and east africa, and on east china. The computer aided mapping of land use and environment is made at different scales. The data base has been done in lanchad, spot simulation and codata programs. At zonal scale, we observe north africa (algeria and tunisia) and sahel by meteosat, and tanzania by noaa-tiros n and meteosat. At regional scale, we observe physical landscape of mopti and bandiagara (mali) by meteosat, landsat mss and sir-a data and by spot simulation; we observe iringa and karema (tanzania) by meteosat, noaa-tiros n and landsat mss and tm data; we observe land use units like rice fields (mopti mali) by spot simulation, irrigated farms in djebel amour (algeria); we observe at regional scale the area of handan-xintai and the hydrological network (china). At urban scales, we observe the morphology of the urban areas of n'djamena (tchad) and annaba (algeria) by landsat and digitized aerial data. We have used automatic preprocessing in edge detection and lineament analysis, and supervised classification in thematic mapping. Ground truth controls have been done in algeria, tchad, mali, tanzania and china. Our aim was to demonstrate the efficiency of multisatellite data processing in the environmental mapping

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Maire, Florian. "Détection et classification de cibles multispectrales dans l'infrarouge." Thesis, Evry, Institut national des télécommunications, 2014. http://www.theses.fr/2014TELE0007/document.

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Les dispositifs de protection de sites sensibles doivent permettre de détecter des menaces potentielles suffisamment à l’avance pour pouvoir mettre en place une stratégie de défense. Dans cette optique, les méthodes de détection et de reconnaissance d’aéronefs se basant sur des images infrarouge multispectrales doivent être adaptées à des images faiblement résolues et être robustes à la variabilité spectrale et spatiale des cibles. Nous mettons au point dans cette thèse, des méthodes statistiques de détection et de reconnaissance d’aéronefs satisfaisant ces contraintes. Tout d’abord, nous spéciﬁons une méthode de détection d’anomalies pour des images multispectrales, combinant un calcul de vraisemblance spectrale avec une étude sur les ensembles de niveaux de la transformée de Mahalanobis de l’image. Cette méthode ne nécessite aucune information a priori sur les aéronefs et nous permet d’identiﬁer les images contenant des cibles. Ces images sont ensuite considérées comme des réalisations d’un modèle statistique d’observations ﬂuctuant spectralement et spatialement autour de formes caractéristiques inconnues. L’estimation des paramètres de ce modèle est réalisée par une nouvelle méthodologie d’apprentissage séquentiel non supervisé pour des modèles à données manquantes que nous avons développée. La mise au point de ce modèle nous permet in ﬁne de proposer une méthode de reconnaissance de cibles basée sur l’estimateur du maximum de vraisemblance a posteriori. Les résultats encourageants, tant en détection qu’en classiﬁcation, justiﬁent l’intérêt du développement de dispositifs permettant l’acquisition d’images multispectrales. Ces méthodes nous ont également permis d’identiﬁer les regroupements de bandes spectrales optimales pour la détection et la reconnaissance d’aéronefs faiblement résolus en infrarouge Surveillance systems should be able to detect potential threats far ahead in order to put forward a defence strategy. In this context, detection and recognition methods making use of multispectral infrared images should cope with low resolution signals and handle both spectral and spatial variability of the targets. We introduce in this PhD thesis a novel statistical methodology to perform aircraft detection and classiﬁcation which take into account these constraints. We ﬁrst propose an anomaly detection method designed for multispectral images, which combines a spectral likelihood measure and a level set study of the image Mahalanobis transform. This technique allows to identify images which feature an anomaly without any prior knowledge on the target. In a second time, these images are used as realizations of a statistical model in which the observations are described as random spectral and spatial deformation of prototype shapes. The model inference, and in particular the prototype shape estimation, is achieved through a novel unsupervised sequential learning algorithm designed for missing data models. This model allows to propose a classiﬁcation algorithm based on maximum a posteriori probability Promising results in detection as well as in classiﬁcation, justify the growing interest surrounding the development of multispectral imaging devices. These methods have also allowed us to identify the optimal infrared spectral band regroupments regarding the low resolution aircraft IRS detection and classiﬁcation

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Mas, Adrien. "Etude et développement de caméras infrarouge multispectrales à acquisition simultanée pour la détection de gaz." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASP001.

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L’émission accidentelle de gaz sur des sites industriels ou l’utilisation d’armes chimiques peuvent avoir des conséquences dramatiques. Bertin Technologies commercialise une caméra multispectrale infrarouge utilisant un détecteur non-refroidi appelée Second Sight permettant de détecter de nombreux gaz. Cependant, l’acquisition temporelle des images spectrales est un frein pour une utilisation sur porteurs mobiles (véhicules, drones…). L’objet de la thèse a donc été d’étudier plusieurs concepts de caméras multispectrales à acquisition simultanée utilisant un seul détecteur non-refroidi. J’ai travaillé sur deux concepts d’architectures optiques : une architecture basée sur l’utilisation d’un kaléidoscope et une architecture multivoies inspiré de l’architecture TOMBO. L’architecture kaléidoscope a l’avantage d’utiliser de manière optimale le détecteur pour de fortes ouvertures et pour une grande variété de champs de vue. Elle est cependant encombrante et la fonction multispectrale reste délicate à intégrer. L’architecture multivoie, quant à elle, est très compacte et facilement adaptable à des applications multispectrales mais un compromis entre le champ de vue et l’ouverture doit être trouvé. Nous avons choisi cette architecture comme successeur de la Second Sight et j’ai pu réaliser un démonstrateur. Enfin, un modèle radiométrique a été développé pour comparer les différentes caméras et j’ai montré que la caméra TOMBO pouvait avoir de meilleures performances que la Second Sight grâce à l’acquisition simultanée des images multispectrales The accidental emission of gas in an industrial platform or the use of chemical weapons can have dramatic consequences. Bertin Technology commercialize an infrared multispectral camera using an array of uncooled detectors and called Second Sight allowing the detection of numerous gas. However, the temporal acquisition of spectral images is a limitation for a use on mobile platforms (vehicles, drones...). Therefore, the purpose of my PhD was to study several concepts of snapshot multispectral cameras using a single array of uncooled detectors. I worked on two concepts of optical architectures: a kaleidoscope-based design and a multichannel design inspired by the TOMBO architecture. The kaleidoscope-based camera can use optimally the focal plane array while having an important aperture and a great range of Fields of View. However, it has an important footprint and the implementation of the multispectral function is not obvious. By comparing, the multichannel architecture can be very compact and easily adaptable for multispectral applications but a compromise between its aperture and its Field Of View is necessary. Following these studies, the TOMBO multichannel design was chosen as the successor of the Second Sight and I could make a first demonstrator. Finally, a radiometric model was developed to compare the different cameras and I showed that the TOMBO camera could have better performances than the Second Sight thanks to its snapshot feature

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Maire, Florian. "Détection et classification de cibles multispectrales dans l'infrarouge." Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2014. http://www.theses.fr/2014TELE0007.

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Les dispositifs de protection de sites sensibles doivent permettre de détecter des menaces potentielles suffisamment à l’avance pour pouvoir mettre en place une stratégie de défense. Dans cette optique, les méthodes de détection et de reconnaissance d’aéronefs se basant sur des images infrarouge multispectrales doivent être adaptées à des images faiblement résolues et être robustes à la variabilité spectrale et spatiale des cibles. Nous mettons au point dans cette thèse, des méthodes statistiques de détection et de reconnaissance d’aéronefs satisfaisant ces contraintes. Tout d’abord, nous spéciﬁons une méthode de détection d’anomalies pour des images multispectrales, combinant un calcul de vraisemblance spectrale avec une étude sur les ensembles de niveaux de la transformée de Mahalanobis de l’image. Cette méthode ne nécessite aucune information a priori sur les aéronefs et nous permet d’identiﬁer les images contenant des cibles. Ces images sont ensuite considérées comme des réalisations d’un modèle statistique d’observations ﬂuctuant spectralement et spatialement autour de formes caractéristiques inconnues. L’estimation des paramètres de ce modèle est réalisée par une nouvelle méthodologie d’apprentissage séquentiel non supervisé pour des modèles à données manquantes que nous avons développée. La mise au point de ce modèle nous permet in ﬁne de proposer une méthode de reconnaissance de cibles basée sur l’estimateur du maximum de vraisemblance a posteriori. Les résultats encourageants, tant en détection qu’en classiﬁcation, justiﬁent l’intérêt du développement de dispositifs permettant l’acquisition d’images multispectrales. Ces méthodes nous ont également permis d’identiﬁer les regroupements de bandes spectrales optimales pour la détection et la reconnaissance d’aéronefs faiblement résolus en infrarouge Surveillance systems should be able to detect potential threats far ahead in order to put forward a defence strategy. In this context, detection and recognition methods making use of multispectral infrared images should cope with low resolution signals and handle both spectral and spatial variability of the targets. We introduce in this PhD thesis a novel statistical methodology to perform aircraft detection and classiﬁcation which take into account these constraints. We ﬁrst propose an anomaly detection method designed for multispectral images, which combines a spectral likelihood measure and a level set study of the image Mahalanobis transform. This technique allows to identify images which feature an anomaly without any prior knowledge on the target. In a second time, these images are used as realizations of a statistical model in which the observations are described as random spectral and spatial deformation of prototype shapes. The model inference, and in particular the prototype shape estimation, is achieved through a novel unsupervised sequential learning algorithm designed for missing data models. This model allows to propose a classiﬁcation algorithm based on maximum a posteriori probability Promising results in detection as well as in classiﬁcation, justify the growing interest surrounding the development of multispectral imaging devices. These methods have also allowed us to identify the optimal infrared spectral band regroupments regarding the low resolution aircraft IRS detection and classiﬁcation

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Munechika, Curtis K. "Merging panchromatic and multispectral images for enhanced image analysis /." Online version of thesis, 1990. http://hdl.handle.net/1850/11366.

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Wahham, Atheer. "Multispectral Image Acquisition." Thesis, Linköpings universitet, Institutionen för teknik och naturvetenskap, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-97053.

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The purpose of this project was to develop control software for a multi-spectral imaging system. The multi-spectral imaging system used by the colour Lab consists of a camera (Alta USB camera) and a filter (VariSpec liquid crystal tuneable filter). The camera and the filter were delivered by two different manufacturers and therefore have two separate stand-alone control programs. The fact that the hardware had to be controlled by two separate pieces of software meant that the image capturing procedure was very time-consuming and needed an unrealistic amount of user input. The project resulted in a C++ console program with all the required and necessary functionsas those provided by the individual software, camera and filter; and operated both the camera and the filter simultaneously and conveniently. The project was performed at the Norwegian colour Laboratory in Gjøvik University College.

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Martin, Benoit. "Méthode d'optimisation mixte bio-inspirée : application à l'imagerie multi-spectrale et à la mesure d'audience." Thesis, Ecole centrale de Marseille, 2018. http://www.theses.fr/2018ECDM0008.

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Cette thèse propose une nouvelle méthode d’optimisation bio-inspirée basée sur le GWO avec pour but de pouvoir résoudre des problèmes d’optimisation dits mixtes, c’est-à-dire des problèmes composés de variables continues et discrètes. Cette nouvelle méthode baptisée mixed GWO est ensuite appliquée à 2 problématiques distincts.Tout d’abord, le mixed GWO pourra permettre d’améliorer la qualité de la classification d’image par SVM. En effet, la fiabilité d’un SVM va dépendre de ses paramètres d’entraînement, et il n’existe pas de méthode non empirique et non exhaustive permettant de définir ces paramètres pour un problème de classification donné. Le mixed GWO se propose comme une solution à ce problème de paramétrage. La classification doit permettre à l’entreprise IntuiSense d’ajouter une brique de reconnaissance de genre à son outil de mesure d’audience ISAM.Ensuite, le mixedGWO est employé pour faire du débruitage et du démêlage de spectres en simultanée sur des images multi-spectrales ou hyper-spectrales. En effet, la qualité du démêlage des spectres va être particulièrement dépendant de la qualité du débruitage de l’image : faire ces 2 étapes simultanément permet donc un gain de temps et une fiabilité des résultats bien plus intéressants que les faire l’une après l’autre This thesis proposes a novel bio-inspired optimization method based on the GWOalgorithm, with the purpose of solving mixed optimization problems, i.e. problems with bothcontinuous and discrete variables. This novel method is named mixedGWO and is applied to2 distinct problematics.Firstly, the mixedGWO should permit to improve the quality of image classification bySVM. Indeed, a SVM accuracy will depend of its training parameters, and there is nonempirical and non exhaustive method to define these parameters for a given classificationproblem. Therefore, the mixedGWO can be used as a solution to this parametring problem.The improve classification should allow the company IntuiSense to add the gender recognition feature to its audience measurement tool ISAM.Secondly, the mixedGWO is used for joint denoising and unmixing of spectra in multispectral and hyper-spectral image processing. Indeed, the unmixing’s quality is stronglydependent of the denoising quality : doing these 2 steps simultaneously permits a gain oftime and a results’ accuracy way better than if they are done one after the other

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Renaud, Rémi. "Développement de l'imagerie multispectrale plein champ pour l'étude de l'activation cérébrale in vivo." Thesis, Paris 11, 2012. http://www.theses.fr/2012PA112240.

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L'imagerie optique multispectrale du signal intrinsèque permet d'estimer les variations des paramètres hémodynamiques à partir de la collecte des fluctuations de réflectance, à au moins deux longueurs d'onde, induites par une activation cérébrale. Cette thèse propose une étude méthodologique et instrumentale mais aussi une validation in vivo des développements entrepris. Le calcul des paramètres hémodynamiques nécessite l'application d'une loi de Beer-Lambert modifiée introduisant un terme crucial pour la précision du calcul des variations des paramètres hémodynamiques, le DP, que nous avons estimé par simulation Monte Carlo pour les modèles du cortex somatosensoriel et du bulbe olfactif de rat. Nous montrons ainsi que les variations d'absorption, de diffusion ou d'anisotropie n'influe pas sur les valeurs de DP en dessous de 630 nm, que la géométrie et les propriétés optiques des structures a un impact sur celles-ci. Ainsi, le calcul des DP pour chaque structure cérébrale est indispensable. En outre, le choix des longueurs d'onde d'illumination est décisif et s'apprécie en fonction de deux paramètres, la diaphonie et le séparabilité qui ont été calculés pour déterminer les couples et les triplets de longueurs d'onde optimaux pour l'étude du bulbe olfactif de rat. Il apparaît que les valeurs de séparabilité sont négligeables en raison de la forte absorptivité des tissus biologiques dans le visible et que le choix des combinaisons optimales peut se faire en se basant seulement sur les valeurs de diaphonie. La deuxième étape a consisté à construire un banc d'imagerie multispectrale performant et à le valider ainsi que l'étude méthodologique. Les résultats in vivo montrent une différence flagrante des signaux de réflectance et hémodynamiques entre le cortex somatosensoriel et le bulbe olfactif dont l'origine physique et/ou biologique est discutée Multispectral imaging of intrinsic optical signal allows to estimate changes in hemodynamic parameters from the collection of reflectance fluctuations, at least with two wavelengths, induced by cerebral activation. This thesis proposes methodological and instrumental studies but also in vivo validation of developments undertaken. The calculation of hemodynamic parameters requires the application of a modified Beer-Lambert law introducing a crucial term for accuracy of hemodynamic parameters changes calculation, the DP, which had been estimated using Monte Carlo simulation models of the somatosensory cortex and olfactory bulb of rats. We show that the variations of absorption, diffusion or anisotropy does not affect the values of DP, whereas geometry and optical properties of the structures have an great impact on them. Thus, calculation of DP for each studied brain structure is essential. In addition, the choice of wavelength illumination is critical and appreciated in terms of two parameters, crosstalk and separability. Pairs and triplets of optimal wavelengths for rat olfactory bulb study were calculated. It appears that the separability values are negligible due to the high absorptivity of biological tissues in the visible and the choice of optimal combinations can be based only on the values of crosstalk. The second step was to build a bench multispectral imaging performance, to validate it and methodological study. The results show a striking difference hemodynamic and reflectance signals between somatosensory cortex and olfactory bulb, which physical origin and/or biological is discussed

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Matanga, Jacques. "STUDY AND REALIZATION OF A MULTISPETRAL DETECTOR(FILTER) BY NON DESTRUCTIVE SPECTRAL DISPERSION THROUGH TE NANOSTRUCTURE FILM." Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCK019.

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Le développement des techniques d’imageries multispectral, d’holographie et de lithographie permet d’exploiter les propriétés des réseaux diffractant dans une grande variété de composants photoniques. Ils sont incorporés dans des diodes laser comme réflecteurs de Bragg distribués, dans différentes fonctions d’optique intégrée pour le multiplexage en longueur d’onde ou les interconnexions optiques, ou inscrits au sein même des fibres, conduisant à une grande variété de capteurs pour la détection d’éléments chimiques, la mesure des températures, des pressions, des accélérations d’acquisition et ou de restitution d’images multispectrales etc... [Lee et al. 2007] [Pagnoux et al. 2005].Parmi ces dispositifs, les réseaux résonnants suscitent un très vif intérêt car ils permettent d’obtenir des filtres ultra-sélectifs à partir d’une structure relativement simple. Cette structure est constituée par un guide diélectrique sur lequel est gravé un réseau sub-longueur d’onde de faible profondeur et ou épaisseur. Hors résonance, la structure réfléchit et transmet la lumière selon les propriétés de réflectivité et transmission très proches de celles du dioptre constitué par l’empilement de couches diélectriques The development of multispectral imaging, holography and lithography techniques exploits the properties of diffracting arrays in a wide variety of photonic components. They are incorporated in laser diodes as distributed Bragg reflectors, in various integrated optical functions for wavelength division multiplexing or optical interconnections, or inscribed within the fibers themselves, leading to a wide variety of sensors for detection of chemical elements, measurement of temperatures, pressures, accelerations of acquisition and or restitution of multispectral images, etc. [Lee et al. 2007] [Pagnoux et al. 2005].Among these devices, the resonant networks arouse a great interest because they allow to obtain ultra-selective filters from a relatively simple structure. This structure consists of a dielectric guide on which is etched a subwavelength network of shallow depth and thickness. Except resonance, the structure reflects and transmits the light according to the properties of reflectivity and transmission very close to those of the diopter constituted by the stack of dielectric layers.This work presents the experimental and theoretical studies carried out to overcome the technological obstacles inherent to the realization of thin-film multispectal optical filters.The aim of this thesis is to study and design ultra-selective optical filters based on nanoscale thin films, by exploiting a resonant network structure conceived by depositing multilayer nanowires of metamaterials to surpass the performances of the current filters. Particular in the field of their spectral characteristics and their sensitivity to polarization. An issue of the study is to develop the associated manufacturing process, to identify the technological limitations imposed by the state of the art, to propose a reproducible process and if possible compatible with a collective technological development and low cost.The second was to use the samples from the fabrication of the diffraction gratings to associate it with a tri-CCD transistor-based sensor in the LE2I laboratory, in order to design a sharp acquisition device in multispectral imaging and of vision.The analysis of experimental performances, confronted with theoretical predictions and technological limitations, must lead to a realistic estimate of the potentialities of the proposed filters. To do this we began our study with a literature review on all the key elements of the subject, Nanotechnology, nanoscience these advantages these disadvantages, these possibilities. A review of the literature on multispectral imaging and these ascendants

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Choate, Laura, Kevin Lundstrom, Kevin Pounds, Garrett Richards, and Eli Vinal. "Remote Imaging System Acquisition Multispectral Imager." International Foundation for Telemetering, 2011. http://hdl.handle.net/10150/595725.

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ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada The National Aeronautics and Space Administration's (NASA) Remote Imaging System Acquisition (RISA) camera will integrate the functionalities of existing space cameras. The system operates between 350nm and 1050nm wavelengths, with a MATLAB user interface, uses a CS-mount standard with a CMOS detector, and has a fixed focal plane. The implementation of a liquid lens uses electrical focus adjustments to image from infinity down to one foot. This will allow wireless operation and reduces mechanical failure. All images and video captured will be transmitted wirelessly to a MATLAB program. This data is then processed and stored, allowing for remote imaging.

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Dissertations / Theses on the topic 'Multispectral imagery'

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