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Dissertations / Theses on the topic 'HYPER SPECTRAL IMAGE CLASSIFICATION'

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Published: 11 September 2023

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1

Kliman, Douglas Hartley. "Rule-based classification of hyper-temporal, multi-spectral satellite imagery for land-cover mapping and monitoring." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/187473.

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A rule-based classification model was developed to derive land-cover information from a large set of hyper-temporal, multi-spectral satellite imagery encompassing the state of Arizona. The model uses Advanced Very High Resolution Radiometer (AVHRR) imagery and the 30-minute digital elevation model (DEM) from the EROS Data Center (EDC) Conterminous U.S. AVHRR Biweekly Composites. Sixty one images from 1990, 1991 and 1992 were analyzed using the Brown & Lowe (1973) Natural Vegetative Communities of Arizona map to identify temporal patterns of Normalized Difference Vegetation Index (NDVI) and the
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2

Falco, Nicola. "Advanced Spectral and Spatial Techniques for Hyperspectral Image Analysis and Classification." Doctoral thesis, Università degli studi di Trento, 2015. https://hdl.handle.net/11572/369072.

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Recent advances in sensor technology have led to an increased availability of hyperspectral remote sensing images with high spectral and spatial resolutions. These images are composed by hundreds of contiguous spectral channels, covering a wide spectral range of frequencies, in which each pixel contains a highly detailed representation of the reflectance of the materials present on the ground, and a better characterization in terms of geometrical detail. The burst of informative content conveyed in the hyperspectral images permits an improved characterization of different land coverages. In sp
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Falco, Nicola. "Advanced Spectral and Spatial Techniques for Hyperspectral Image Analysis and Classification." Doctoral thesis, University of Trento, 2015. http://eprints-phd.biblio.unitn.it/1421/1/PhD_Nicola_Trento.pdf.

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Recent advances in sensor technology have led to an increased availability of hyperspectral remote sensing images with high spectral and spatial resolutions. These images are composed by hundreds of contiguous spectral channels, covering a wide spectral range of frequencies, in which each pixel contains a highly detailed representation of the reflectance of the materials present on the ground, and a better characterization in terms of geometrical detail. The burst of informative content conveyed in the hyperspectral images permits an improved characterization of different land coverages. In s
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Jia, Xiuping Electrical Engineering Australian Defence Force Academy UNSW. "Classification techniques for hyperspectral remote sensing image data." Awarded by:University of New South Wales - Australian Defence Force Academy. School of Electrical Engineering, 1996. http://handle.unsw.edu.au/1959.4/38713.

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Hyperspectral remote sensing image data, such as that recorded by AVIRIS with 224 spectral bands, provides rich information on ground cover types. However, it presents new problems in machine assisted interpretation, mainly in long processing times and the difficulties of class training due to the low ratio of number of training samples to the number of bands. This thesis investigates feasible and efficient feature reduction and image classification techniques which are appropriate for hyperspectral image data. The study is reported in three parts. The first concerns a deterministic approach
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Prasert, Sunyaruk. "Multi angle imaging with spectral remote sensing for scene classification." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Mar%5FPrasert.pdf.

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Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, March 2005.<br>Thesis Advisor(s): Richard C. Olsen. Includes bibliographical references (p. 95-97). Also available online.
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Alam, Fahim Irfan. "Deep Feature Learning for Spectral-Spatial Classification of Hyperspectral Remote Sensing Images." Thesis, Griffith University, 2019. http://hdl.handle.net/10072/386535.

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The recent advances in aerial- and satellite-based hyperspectral imaging sensor technologies have led to an increased availability of Earth's images with high spatial and spectral resolution, which opened the door to a large range of important applications. Hyperspectral imaging records detailed spectrum of the received light in each spatial position in the image, in which each pixel contains a highly detailed representation of the reflectance of the materials present on the ground, and a better characterization in terms of geometrical details. Since different substances exhibit different spec
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Hoarau, Romain. "Rendu interactif d'image hyper spectrale par illumination globale pour la prédiction de la signature infrarouge d'aéronefs." Electronic Thesis or Diss., Aix-Marseille, 2019. http://theses.univ-amu.fr.lama.univ-amu.fr/191219_HOARAU_358wfqq893efe918esmfu405fjhqvj_TH.pdf.

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Le dimensionnement de capteur est un enjeu majeur pour le domaine de la détection d'aéronefs. Dans cette optique, il est nécessaire de simuler ces capteurs via des modèles et un nombre conséquent d'images spectrales d'aéronefs. L'obtention de ces images via des campagnes aériennes de mesure est toutefois onéreuse et difficile. Une simulation de ces données s'impose donc. Afin de répondre à ces besoins, des algorithmes d'illumination globale à haute dimension spectrale sont utilisés. Dans ces conditions, ces algorithmes posent des problèmes de consommation mémoire et de temps de calcul. Le proj
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Behmo, Régis. "Visual feature graphs and image recognition." Phd thesis, Ecole Centrale Paris, 2010. http://tel.archives-ouvertes.fr/tel-00545419.

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La problèmatique dont nous nous occupons dans cette thèse est la classification automatique d'images bidimensionnelles, ainsi que la détection d'objets génériques dans des images. Les avancées de ce champ de recherche contribuent à l'élaboration de systèmes intelligents, tels que des robots autonomes et la création d'un web sémantique. Dans ce contexte, la conception de représentations d'images et de classificateurs appropriés constituent des problèmes ambitieux. Notre travail de recherche fournit des solutions à ces deux problèmes, que sont la représentation et la classification d'images. Afi
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9

Tso, Brandt C. K. "An investigation of alternative strategies for incorporating spectral, textural, and contextual information in remote sensing image classification." Thesis, University of Nottingham, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.387663.

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10

Rajadell, Rojas Olga. "Data selection and spectral-spatial characterisation for hyperspectral image segmentation. Applications to remote sensing." Doctoral thesis, Universitat Jaume I, 2013. http://hdl.handle.net/10803/669093.

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El análisis de imágenes ha impulsado muchos descubrimientos en la ciencia actual. Esta tesis se centra en el análisis de imágenes remotas para inspección aérea, exactamente en el problema de segmentación y clasificación de acuerdo al uso del suelo. Desde el nacimiento de los sensores hiperespectrales su uso ha sido vital para esta tarea ya que facilitan y mejoran sustancialmente el resultado. Sin embargo el uso de imágenes hiperespectrales entraña, entre otros, problemas de dimensionalidad y de interacción con los expertos. Proponemos mejoras que ayuden a paliar estos inconvenientes y hagan
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11

Teresi, Michael Bryan. "Multispectral Image Labeling for Unmanned Ground Vehicle Environments." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/53998.

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Described is the development of a multispectral image labeling system with emphasis on Unmanned Ground Vehicles(UGVs). UGVs operating in unstructured environments face significant problems detecting viable paths when LIDAR is the sole source for perception. Promising advances in computer vision and machine learning has shown that multispectral imagery can be effective at detecting materials in unstructured environments [1][2][3][4][5][6]. This thesis seeks to extend previous work[6][7] by performing pixel level classification with multispectral features and texture. First the images are spatia
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Key, Thomas Lee. "An evaluation of the relative value of spectral and phenological information for tree crown classification of digital images in the eastern deciduous forest /." Morgantown, W. Va. : [West Virginia University Libraries], 1998. http://etd.wvu.edu/templates/showETD.cfm?recnum=107.

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Thesis (M.A.)--West Virginia University, 1998.<br>Title from document title page. Document formatted into pages; contains viii, 51 p. : col. ill., col. map. Vita. Includes abstract. Includes bibliographical references (p. 32-34).
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Wondim, Yonas kassaw. "Hyperspectral Image Analysis Algorithm for Characterizing Human Tissue." Thesis, Linköpings universitet, Biomedicinsk instrumentteknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-75156.

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AbstractIn the field of Biomedical Optics measurement of tissue optical properties, like absorption, scattering, and reduced scattering coefficient, has gained importance for therapeutic and diagnostic applications. Accuracy in determining the optical properties is of vital importance to quantitatively determine chromophores in tissue.There are different techniques used to quantify tissue chromophores. Reflectance spectroscopy is one of the most common methods to rapidly and accurately characterize the blood amount and oxygen saturation in the microcirculation. With a hyper spectral imaging (H
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Hijazi, Hala. "Proposition d'une méthode spectrale combinée LDA et LLE pour la réduction non-linéaire de dimension : Application à la segmentation d'images couleurs." Thesis, Littoral, 2013. http://www.theses.fr/2013DUNK0516.

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Les méthodes d'analyse de données et d'apprentissage ont connu un développement très important ces dernières années. En effet, après les réseaux de neurones, les machines à noyaux (années 1990), les années 2000 ont vu l'apparition de méthodes spectrales qui ont fourni un cadre mathématique unifié pour développer des méthodes de classification originales. Parmi celles-ci ont peut citer la méthode LLE pour la réduction de dimension non linéaire et la méthode LDA pour la discrimination de classes. Une nouvelle méthode de classification est proposée dans cette thèse, méthode issue d'une combinaiso
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15

Hamed, Nabil. "Conception et realisation d'un systeme de classification en teledetection par combinaison d'analyses radiometriques et spatiales." Université Louis Pasteur (Strasbourg) (1971-2008), 1987. http://www.theses.fr/1987STR13153.

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Lorsque la resolution spatiale devient trop fine, l'utilisation de l'analyse radiometrique pour l'extraction d'informations des images en teledetection est insuffisante. Aussi, pour pallier a ce probleme, on presente une nouvelle classification combinant une analyse spatiale a l'analyse radiometrique
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Green, Christopher Lee. "IP Algorithm Applied to Proteomics Data." Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd618.pdf.

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Linn, Rodrigo de Marsillac. "Avaliação dos modelos de mistura espectral MESMA e SMA aplicados aos dados hiperespectrais Hyperion/EO-1 adquiridos na Planície Costeira do Rio Grande do Sul." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2008. http://hdl.handle.net/10183/23707.

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O objetivo do presente trabalho foi avaliar o uso potencial dos dados hiperespectrais do sensor orbital Hyperion/Earth Observing One (EO-1) e dos modelos de mistura espectral MESMA (Multiple Endmember Spectral Mixture Analysis) e SMA (Spectral Mixture Analysis) para discriminação de classes de cobertura da Planície Costeira do Rio Grande do Sul. O modelo MESMA difere do SMA por permitir que o número e o tipo de Membros de Referência (MRs), assim como sua abundância, variem pixel a pixel. A abordagem metodológica utilizada envolveu as seguintes etapas: (a) préprocessamento dos dados Hyperion e
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18

Karvir, Hrishikesh. "Design and Validation of a Sensor Integration and Feature Fusion Test-Bed for Image-Based Pattern Recognition Applications." Wright State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=wright1291753291.

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19

Teixeira, Karla dos Santos. "Uma proposta metodológica de integração de técnicas de análise espectral e de inteligência computacional, baseadas em conhecimento, para o reconhecimento de padrões em imagens multiespectrais." Universidade do Estado do Rio de Janeiro, 2012. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=5779.

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Somente no ano de 2011 foram adquiridos mais de 1.000TB de novos registros digitais de imagem advindos de Sensoriamento Remoto orbital. Tal gama de registros, que possui uma progressão geométrica crescente, é adicionada, anualmente, a incrível e extraordinária massa de dados de imagens orbitais já existentes da superfície da Terra (adquiridos desde a década de 70 do século passado). Esta quantidade maciça de registros, onde a grande maioria sequer foi processada, requer ferramentas computacionais que permitam o reconhecimento automático de padrões de imagem desejados, de modo a permitir a extr
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Hamilton, Erin Kinzel. "Multiscale and meta-analytic approaches to inference in clinical healthcare data." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47600.

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The field of medicine is regularly faced with the challenge of utilizing information that is complicated or difficult to characterize. Physicians often must use their best judgment in reaching decisions or recommendations for treatment in the clinical setting. The goal of this thesis is to use innovative statistical tools in tackling three specific challenges of this nature from current healthcare applications. The first aim focuses on developing a novel approach to meta-analysis when combining binary data from multiple studies of paired design, particularly in cases of high heterogeneity bet
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Karoui, Moussa Sofiane. "Méthodes de séparation aveugle de sources et application à la télédétection spatiale." Phd thesis, Université Paul Sabatier - Toulouse III, 2012. http://tel.archives-ouvertes.fr/tel-00790655.

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Cette thèse concerne la séparation aveugle de sources, qui consiste à estimer un ensemble de signaux sources inconnus à partir d'un ensemble de signaux observés qui sont des mélanges à paramètres inconnus de ces signaux sources. C'est dans ce cadre que le travail de recherche de cette thèse concerne le développement et l'utilisation de méthodes linéaires innovantes de séparation de sources pour des applications en imagerie de télédétection spatiale. Des méthodes de séparation de sources sont utilisées pour prétraiter une image multispectrale en vue d'une classification supervisée de ses pixels
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Lu, Liang-You, and 盧亮有. "Application of FABEMD to hyper-spectral image classification." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/43229087812306432050.

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碩士<br>國立中興大學<br>土木工程學系所<br>101<br>Hyperspectral images provide a great number of spectral information and have been broadly applied to image classifications. However, the scattered pixel problem due to atmosphere noises and incomplete classification leading unsatisfactory classification accuracy remains to be solved. A denoising process includes noise detection and deletion. This paper integrates Fast and Adaptive Bi-dimensional Emperical Mode Decomposition (FABEMD) and Minimum Noise Fraction (MNF) as a two-step denoising process to improve classification accuracy on a hyperspectral image. Reg
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THAPLIYAL, ANKITA. "CONVOLUTIONAL NETWORK FEATURE HIERARCHY FOR HYPER SPECTRAL IMAGE CLASSIFICATION." Thesis, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/20109.

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Hyper spectral image classification is the recent technology that is famous among the researchers nowadays. It is simply an application of remote sensing methodology. The results of remote sensing are basically needs to get studied by the scientists properly so that they can analyze the surface area and the target information accordingly. Then next to the study of target information further conclusions can be made about that area successfully. Remote sensing is the first step to analyze the whole process in which the satellite helps to provide several images of a particular land ar
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He, Yuan. "Hyper-spectral image processing using high performance reconfigurable computers." 2004. http://etd.utk.edu/2004/HeYuan.pdf.

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Thesis (M.S.)--University of Tennessee, Knoxville, 2004.<br>Title from title page screen (viewed May 17, 2004). Thesis advisor: Gregory Peterson. Document formatted into pages (x, 123 p. : col. ill.). Vita. Includes bibliographical references (p. 74-77).
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Zambon, Francesca. "Spectral Analysis and Classification of Hyper- and Multispectral Data of Planetary Surfaces." Tesi di dottorato, 2014. http://www.fedoa.unina.it/9846/1/tesi_dottorato_zambon.pdf.

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L’obiettivo principale della Tesi di Dottorato è stato quello di utilizzare diverse tecniche di analisi per elaborare ed estrarre informazioni da dati multispettrali e iperspettrali di superfici planetarie provenienti da missioni spaziali. Sono stati analizzati i dati forniti dallo spettrometro (MASCS) e della camera (MDIS) a bordo della missione Messanger, dedicata a Mercurio e quelli dello spettrometro VIR a bordo della missione Dawn volta allo studio degli asteroidi Vesta e Cerere. Sono stati analizzati e classificati i dati di VIRS e MDIS traminte due metodi di classificazione: ISODATA e i
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Liang, Jie. "Spectral-spatial Feature Extraction for Hyperspectral Image Classification." Phd thesis, 2016. http://hdl.handle.net/1885/111995.

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As an emerging technology, hyperspectral imaging provides huge opportunities in both remote sensing and computer vision. The advantage of hyperspectral imaging comes from the high resolution and wide range in the electromagnetic spectral domain which reflects the intrinsic properties of object materials. By combining spatial and spectral information, it is possible to extract more comprehensive and discriminative representation for objects of interest than traditional methods, thus facilitating the basic pattern recognition tasks, such as object detectio
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Senapati, Subhrajyoti. "Unsupervised Classification of Hyperspectral Images based on Spectral Features." Thesis, 2015. http://ethesis.nitrkl.ac.in/7177/1/Unsupervised_Senapati_2015.pdf.

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In this world of Big Data, large quantities of data are been created everyday from all the type of visual sensors available in the hands of mankind. One important data is that we obtain from satellite of the land image. The application of these data are numerous. They have been used in classification of land regions, change detection of an area over a period of time, detecting different anomalies in the area and so on. As data is increasing at a high rate, so manually doing these jobs is not a good idea. So, we have to apply automated algorithms to solve these jobs. The images we see generally
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Du, Zheng. "Integration of Spatial and Spectral Information for Hyperspectral Image Classification." 2008. http://trace.tennessee.edu/utk_graddiss/431.

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Hyperspectral imaging has become a powerful tool in biomedical and agriculture fields in the recent years and the interest amongst researchers has increased immensely. Hyperspectral imaging combines conventional imaging and spectroscopy to acquire both spatial and spectral information from an object. Consequently, a hyperspectral image data contains not only spectral information of objects, but also the spatial arrangement of objects. Information captured in neighboring locations may provide useful supplementary knowledge for analysis. Therefore, this dissertation investigates the integration
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Schwartzkopf, Wade Carl. "Maximum likelihood techniques for joint segmentation-classification of multi-spectral chromosome images." Thesis, 2002. http://wwwlib.umi.com/cr/utexas/fullcit?p3110690.

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Lu, Wern Horn, and 盧文鴻. "A Study of Applying Hyper-Rectangle Learning Model to Interpret the Classification of Remote Sensing Image." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/95933853781797954300.

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碩士<br>中華大學<br>土木工程學系碩士班<br>88<br>Abstract Recently, many nations comprehensively apply remote sensing method, to serve as the important data resource of analysis and decision planning. The application of this in this aspect has also been more and more popular. The remote sensing data coverage is provided with both comprehensive and up-to-date characteristics, able to serve as a kind of effective survey tool for build environmental resource database with convenient service. This research attempts to engage in image classification with the Hyper- Rectangles Learning Model
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Chang, Chao-Chun, and 張超群. "Mathematical Model Integrating Spectral and Spatial Information for Remotely Sensed Hyperspectral Image Classification." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/95361932830476596947.

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碩士<br>國立臺中教育大學<br>數學教育學系<br>103<br>Hyperspectral image data with hundreds of measured bands potentially provide more accurate and detailed spectral information for classification. However, hyperspectral image with pixel location can provide additional accurate and detailed spatial information for classification, due to the data points of each class tended to form a cluster by its spatial information. Therefore, hyperspectral remote sensing image classification integrating spectral and spatial information is a popular issue in recent years. Hence, in this study, two methods utilizing both spec
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Cheng, Ying-Ying, and 鄭盈盈. "Hyperspectral image classification via integration of joint sparse representation with spectral and spatial information." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/7egfn5.

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碩士<br>國立臺灣大學<br>土木工程學研究所<br>107<br>Machine learning algorithms using self-learning to improve performance have become increasingly popular in the processing and analysis of remote sensing image data. The advantage of machine learning is that it is not necessary to know the prior characteristics of data in advance, and the data distribution does not have to be normally distributed, so it is more able to describe the actual distribution of remote sensing image data. Most important information of high-dimensional data (e.g. hyperspectral images) is mainly clustered in low-dimensional subspace. Mo
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"Image classification of spatially heterogeneous land use type based on structural composition of spectral classes." Chinese University of Hong Kong, 1991. http://library.cuhk.edu.hk/record=b5886954.

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Chan, King-Chong.<br>Thesis (M.Phil.) -- Chinese University of Hong Kong, 1991.<br>Bibliography: leaves 150-163.<br>Abstract --- p.i<br>Acknowledgements --- p.ii<br>Figures --- p.vii<br>Tables --- p.x<br>Chapter Chapter 1 --- Introduction --- p.i<br>Chapter 1.1 --- Background --- p.2<br>Chapter 1.2 --- Objectives --- p.5<br>Chapter 1.3 --- Hypotheses --- p.6<br>Chapter 1.4 --- Organization of the Thesis --- p.6<br>Chapter Chapter 2 --- Literature Review --- p.8<br>Chapter 2.1 --- Land Use and Land Cover --- p.10<br>Chapter 2.2 --- Informational Classes and Spectra I Classes --- p.1
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Luu, Thi Phuong Mai. "Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam." Master's thesis, 2009. http://hdl.handle.net/10362/2634.

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies<br>Wetland is one of the most valuable ecological systems in nature. Wetland habitat is a set of comprehensive information of wetland distribution, wetland habitat types are essential to wetland management programs. Maps of wetland should provide sufficient detail, retain an appropriate scale and be useful for further mapping and inventory work (Queensland wetland framework). Remotely sensed image classification techniques are useful to detect vegetation pattern
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王欣萍. "A Study of Spectral Feature Extraction Methods for Crops Classification Base on WorldView-2 Image." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/81627368686318529008.

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碩士<br>逢甲大學<br>都市計畫與空間資訊學系<br>103<br>Automatically classification is the most popular method to do classifying on satellite image, and there have high ratio to use multispectral images on automatically classification in the past. Nevertheless, multispectral images has less spectral information, floristic composition has similar spectral characteristic curve is tough to be discriminated so that it just can discriminate between vegetation and non-vegetation, and can’t ascertain crop classes of farmland fields precisely and attentively, it’s still not enough to achieve the demand of agriculture ma
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Zhang, Qiang Liu Xiuwen. "Appearance-based classification and recognition using spectral histogram representations and hierarchical learning for OCA." Diss., 2005. http://etd.lib.fsu.edu/theses/available/etd-04082005-133212/.

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Thesis (M.S.)--Florida State University, 2005.<br>Advisor: Dr. Xiuwen Liu, Florida State University, College of Arts and Sciences, Dept. of Computer Science. Title and description from dissertation home page (viewed June 10, 2005). Document formatted into pages; contains x, 50 pages. Includes bibliographical references.
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Chang, Chia-Hao, and 張嘉豪. "Fusion of Synthetic Aperture Radar Image and Satellite Remote Sensing Multi-spectral Images on Forest Land Cover Classification." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/53083677850221470277.

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碩士<br>國立屏東科技大學<br>森林系所<br>102<br>Forest inventory requires considerable manpower and material resources. Therefore, using the remote sensing techniques and field surveying to reduce inventory cost and promote the efficiency is a common method in forest inventory. Remote sensing includes active radar sensor data and passive optical sensor data. These sensors provide different information, therefor integration two different type images which can be beneficial for many applications, such as environmental change research, disaster monitoring, land cover classification, and vegetation regeneration.
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Fauvel, Mathieu. "Spectral and Spatial Methods for the Classification of Urban Remote Sensing Data." Phd thesis, 2007. http://tel.archives-ouvertes.fr/tel-00258717.

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Lors de ces travaux, nous nous sommes intéressés au problème de la classification supervisée d'images satellitaires de<br /> zones urbaines. Les données traitées sont des images optiques à très hautes résolutions spatiales: données panchromatiques à très haute résolution spatiale (IKONOS, QUICKBIRD, simulations PLEIADES) et des images hyperspectrales (DAIS, ROSIS).<br />Deux stratégies ont été proposées.<br />La première stratégie consiste en une phase d'extraction de caractéristiques spatiales et spectrales suivie d'une phase de classification. Ces caractéristiques sont extraites par filtrage
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Tung, Do Thanh, and 杜青松. "Assessment of the Grey-Level Co-occurrence Matrix for Land Use/Land Cover Classification using Multi-spectral UAV Image." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/9mw9xe.

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碩士<br>逢甲大學<br>都市計畫與空間資訊學系<br>104<br>The application of UAV has been popular in recent years due to their advantages. The UAV systems are more advantageous as compared with other manned aircraft systems. The main advantages of UAV systems are that they can fly in high risk location, unreachable areas, and at very low altitude close to the objects without threatening human life. Moreover, the UAV images also can exhibit ground surface characteristics in very high spatial resolution. Thus, the level of detail present in the UAV image has increased considerably when compared to the other multispec
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Hung, Mi-Chi, and 洪蜜琪. "Integration of Spectral and Spatial Information in Image Classification- An Application of the Cover and Management Factor (C Value)." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/79115002930716131454.

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碩士<br>中興大學<br>土木工程學系所<br>95<br>Located in sub-tropical and seimic areas, Taiwan frequently bears the severe threats from both typhoons and earthquakes, which could induce debris flows and landslides. The occurrence of landslide is mostly related with the land cover, so how to efficiently acquire the information of the land cover is the critical issue of disaster mitigation. Traditionally it spends a lot of manpower and time to survey the land cover by in situ investigation. In order to get the classifications of land cover rapidly and timely, this research integrates Maximum Likelihood Method
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"Clinically Relevant Classification and Retrieval of Diabetic Retinopathy Images." Master's thesis, 2012. http://hdl.handle.net/2286/R.I.15144.

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abstract: Diabetic retinopathy (DR) is a common cause of blindness occurring due to prolonged presence of diabetes. The risk of developing DR or having the disease progress is increasing over time. Despite advances in diabetes care over the years, DR remains a vision-threatening complication and one of the leading causes of blindness among American adults. Recent studies have shown that diagnosis based on digital retinal imaging has potential benefits over traditional face-to-face evaluation. Yet there is a dearth of computer-based systems that can match the level of performance achieved by op
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Chan, Ching-Yi, and 詹靜怡. "Using Satellite Remote Sensing Multi-Spectral Image for Classification of Forest Fire Severity and Vegetation Recovery in Huanshan Area of Taichung." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/69154386209916747059.

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碩士<br>國立屏東科技大學<br>森林系所<br>100<br>Monitoring the ecological change via post fire after forest fire is an important issue in forest conservation. The spatial model of forest fire severity had been developed by the establishment of the relational model of burned- site land cover and satellite vegetation index. The red and near-infrared band multi-spectral satellite images, which were used to estimate the vegetation index and to discriminate analysis to develop forest fire severity, showed a higher discriminative rate. This study used the Landsat 7 ETM + infrared band (band 7,2.08 -2.35 μm) to cla
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Omran, Mahamed G. H. "Particle swarm optimization methods for pattern recognition and image processing." Thesis, 2005. http://hdl.handle.net/2263/29826.

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Pattern recognition has as its objective to classify objects into different categories and classes. It is a fundamental component of artificial intelligence and computer vision. This thesis investigates the application of an efficient optimization method, known as Particle Swarm Optimization (PSO), to the field of pattern recognition and image processing. First a clustering method that is based on PSO is proposed. The application of the proposed clustering algorithm to the problem of unsupervised classification and segmentation of images is investigated. A new automatic image generation tool t
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Χριστούλας, Γεώργιος. "Ανάπτυξη συστήματος επεξεργασίας δεδομένων τηλεπισκόπησης για αυτόματη ανίχνευση και ταξινόμηση περιοχών με περιβαλλοντικές αλλοιώσεις". Thesis, 2012. http://hdl.handle.net/10889/5312.

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Η παρούσα διατριβή είχε σαν κύριο στόχο την ανάλυση και επεξεργασία των δεδομένων SAR υπό το πρίσμα του περιεχομένου υφής για την ανίχνευση περιοχών με περιβαλλοντικές αλλοιώσεις όπως είναι οι παράνομες εναποθέσεις απορριμμάτων. Τα δεδομένα που χρησιμοποιήθηκαν προέρχονταν από τον δορυφόρο ENVISAT και το όργανο ASAR του Ευρωπαϊκού Οργανισμού Διαστήματος με διακριτική ικανότητα 12.5m και 30m για τις λειτουργίες μονής και διπλής πολικότητας αντίστοιχα καθώς και από τον δορυφόρο Terra-SAR με διακριτική ικανότητα 3m και HH πολικότητα. Χρησιμοποιήθηκαν κλασσικές τεχνικές ανάλυσης και ταξινόμησης υφ
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Strothmann, Wolfram. "Multi-wavelength laser line profile sensing for agricultural applications." Doctoral thesis, 2016. https://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-2016110315110.

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This dissertation elaborates on the novel sensing approach of multi-wavelength laser line profiling (MWLP). It is a novel sensor concept that expands on the well-known and broadly adopted laser line profile sensing concept for triangulation-based range imaging. Thereby, the MWLP concept does not just use one line laser but multiple line lasers at different wavelengths scanned by a single monochrome imager. Moreover, it collects not only the 3D distance values but also reflection intensity and backscattering of the laser lines are evaluated. The system collects spectrally selective image-based
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