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Relevant bibliographies by topics / Near infrared imagery

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Academic literature on the topic 'Near infrared imagery'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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Journal articles on the topic "Near infrared imagery"

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Aden, S. T., J. P. Bialas, Z. Champion, E. Levin, and J. L. McCarty. "Low cost infrared and near infrared sensors for UAVs." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1 (November 7, 2014): 1–7. http://dx.doi.org/10.5194/isprsarchives-xl-1-1-2014.

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Thermal remote sensing has a wide range of applications, though the extent of its use is inhibited by cost. Robotic and computer components are now widely available to consumers on a scale that makes thermal data a readily accessible resource. In this project, thermal imagery collected via a lightweight remote sensing Unmanned Aerial Vehicle (UAV) was used to create a surface temperature map for the purpose of providing wildland firefighting crews with a cost-effective and time-saving resource. The UAV system proved to be flexible, allowing for customized sensor packages to be designed that co

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Adamopoulos, Efstathios, and Fulvio Rinaudo. "Enhancing Image-Based Multiscale Heritage Recording with Near-Infrared Data." ISPRS International Journal of Geo-Information 9, no. 4 (2020): 269. http://dx.doi.org/10.3390/ijgi9040269.

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Passive sensors, operating in the visible (VIS) spectrum, have widely been used towards the trans-disciplinary documentation, understanding, and protection of tangible cultural heritage (CH). Although, many heritage science fields benefit significantly from additional information that can be acquired in the near-infrared (NIR) spectrum. NIR imagery, captured for heritage applications, has been mostly investigated with two-dimensional (2D) approaches or by 2D-to-three-dimensional (3D) integrations following complicated techniques, including expensive imaging sensors and setups. The availability

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Pisano, Andrea, Francesco Bignami, and Rosalia Santoleri. "Oil Spill Detection in Glint-Contaminated Near-Infrared MODIS Imagery." Remote Sensing 7, no. 1 (2015): 1112–34. http://dx.doi.org/10.3390/rs70101112.

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Mantecón, Tomás, Carlos R. del-Blanco, Fernando Jaureguizar, and Narciso García. "A real-time gesture recognition system using near-infrared imagery." PLOS ONE 14, no. 10 (2019): e0223320. http://dx.doi.org/10.1371/journal.pone.0223320.

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Stutte, G. W., and C. A. Stutte. "Use of Near-Infrared video for Localizing Nitrogen Stress in Peach Orchards." HortTechnology 2, no. 2 (1992): 224–27. http://dx.doi.org/10.21273/horttech.2.2.224.

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Computer analysis of airborne, broad-band, near-infrared (NIR, 710 to 1100 nm) video imagery of peach tree canopies was used to determine spatial variability of cumulative stress in two peach orchards. A significant quadratic correlation was found between leaf-N content and the normalized mean pixel intensity (MPI) of the digital imagery of NIR canopy reflectance. This correlation was used to establish MPI estimates of N-stressed trees in the orchard. The relationship was used to localize site-specific spatial variability in a commercial peach orchard. The underlying soil type was found to be

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Coustenis, Athena, Emmanuel Lellouch, Michel Combes, Renald Wittemberg, Christopher P. McKay, and Jean-Pierre Maillard. "Titan’s Atmosphere and Surface from Infrared Spectroscopy and Imagery." International Astronomical Union Colloquium 161 (January 1997): 227–34. http://dx.doi.org/10.1017/s0252921100014743.

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AbstractWe have performed observations of Titan in the near-infrared since 1991, using both spectroscopy and imagery. A higher geometric albedo is observed near the Greatest Eastern Elongation than near the Greatest Western Elongation or Conjunctions. The surface is within reach for telescopes at 1.075, 1.28, 1.6 and 2.0 micron, so we simulated Titan’s geometric albedo in order to derive the surface albedo at all longitudes. Titan’s leading hemisphere appears brighter than the trailing one by 20-25% at 1.08; 1.28 and 1.6 μm, and by 35% at 2.0 μm, with spectra compatible with H2O everywhere. We

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Tempest, Gavin, and Gaynor Parfitt. "Imagery Use and Affective Responses During Exercise: An Examination of Cerebral Hemodynamics Using Near-Infrared Spectroscopy." Journal of Sport and Exercise Psychology 35, no. 5 (2013): 503–13. http://dx.doi.org/10.1123/jsep.35.5.503.

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Imagery, as a cognitive strategy, can improve affective responses during moderate-intensity exercise. The effects of imagery at higher intensities of exercise have not been examined. Further, the effect of imagery use and activity in the frontal cortex during exercise is unknown. Using a crossover design (imagery and control), activity of the frontal cortex (reflected by changes in cerebral hemodynamics using near-infrared spectroscopy) and affective responses were measured during exercise at intensities 5% above the ventilatory threshold (VT) and the respiratory compensation point (RCP). Resu

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Everitt, James H., James V. Richerson, Mario A. Alaniz, David E. Escobar, Ricardo Villarreal, and Michael R. Davis. "Light Reflectance Characteristics and Remote Sensing of Big Bend Loco (Astragalus mollissimusvar.earlei) and Wooton Loco (Astragalus wootonii)." Weed Science 42, no. 1 (1994): 115–22. http://dx.doi.org/10.1017/s0043174500084265.

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The high near-infrared reflectance (0.76 to 0.90 μm) of Big Bend loco and Wooton loco contributed significantly to their orange-red and red image tonal responses, respectively, on color-infrared aerial photographs making them distinguishable from associated vegetation and soil. Big Bend loco could also be distinguished on color-infrared and near-infrared black-and-white video imagery where it had distinct red and whitish tonal responses, respectively. Computer analyses of photographic and videographic images showed that Big Bend loco and Wooton loco populations could be quantified from other l

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Everitt, J. H., D. E. Escobar, D. N. Appel, W. G. Riggs, and M. R. Davis. "Using Airborne Digital Imagery for Detecting Oak Wilt Disease." Plant Disease 83, no. 6 (1999): 502–5. http://dx.doi.org/10.1094/pdis.1999.83.6.502.

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Color-infrared (CIR) digital imagery was evaluated as a remote sensing tool for detecting oak wilt disease in live oak (Quercus fusiformis). Aerial CIR digital imagery and CIR photography were obtained concurrently of a live oak forested area in south-central Texas affected by oak wilt. Dead, diseased, and healthy live oak trees could generally be delineated as well in the digital imagery as in the CIR photography. Light reflectance measurements obtained in the field showed that dead, diseased, and healthy trees had different visible and near-infrared reflectance values.

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Bochko, Vladimir, Petri Välisuo, Toni Harju, and Jarmo Alander. "Lower extremity ulcer image segmentation of visual and near-infrared imagery." Skin Research and Technology 16, no. 2 (2010): 190–97. http://dx.doi.org/10.1111/j.1600-0846.2009.00415.x.

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Dissertations / Theses on the topic "Near infrared imagery"

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Costa, Posada Carlos Rufino. "The topographic effect in visible and near infrared satellite imagery." Thesis, University of Cambridge, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.624720.

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Roldan, Stephanie Marie. "Eye Movements and Hemodynamic Response during Emotional Scene Processing: Exploring the Role of Visual Perception in Intrusive Mental Imagery." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/86165.

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Unwanted and distressing visual imagery is a persistent and emotionally taxing symptom characteristic of several mental illnesses, including depression, schizophrenia, and posttraumatic stress disorder. Intrusive imagery symptoms have been linked to maladaptive memory formation, abnormal visual cortical activity during viewing, gaze pattern deficits, and trait characteristics of mental imagery. Emotional valence of visual stimuli has been shown to alter perceptual processes that influence the direction of attention to visual information, which may result in enhanced attention to suboptimal and

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Roth, Guy W., and n/a. "Agronomic measurements to validate airborne video imagery for irrigated cotton management." University of Canberra. Resource and Environmental Sciences, 1993. http://erl.canberra.edu.au./public/adt-AUC20050801.124927.

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Water is a major factor limiting cotton production and farmers must aim to optimise crop water use through timely irrigation scheduling decisions. Airborne video imagery when calibrated with a low density of ground based observations, offers the potential for near real time monitoring of crop condition, through sequential coverages of entire cotton fields. Using commercially available video equipment mounted on a light aircraft images were acquired of field experiments that were established in commercial cotton fields to test if the imagery could monitor changes in crop condition. Ground data

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Lange, Frédéric. "Développement d’un système de Topographie Optique Diffuse résolu en temps et hyperspectral pour la détection de l’activité cérébrale humaine." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI012.

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La Tomographie Optique Diffuse (TOD) est désormais une modalité d’imagerie médicale fonctionnelle reconnue. L’une des applications les plus répandues de cette technique est celle de l’imagerie fonctionnelle cérébrale chez l’Homme. En effet, cette technique présente de nombreux avantages, notamment grâce à la richesse des contrastes optiques accessibles. Néanmoins, certains verrous subsistent et freinent le développement de son utilisation, spécialement pour des applications chez l’Homme adulte en clinique ou dans des conditions particulières comme lors du suivi de l’activité sportive. En effet

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Li, Kefeng. "Biometric person identification using near-infrared hand-dorsa vein images." Thesis, University of Central Lancashire, 2013. http://clok.uclan.ac.uk/9238/.

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Biometric recognition is becoming more and more important with the increasing demand for security, and more usable with the improvement of computer vision as well as pattern recognition technologies. Hand vein patterns have been recognised as a good biometric measure for personal identification due to many excellent characteristics, such as uniqueness and stability, as well as difficulty to copy or forge. This thesis covers all the research and development aspects of a biometric person identification system based on near-infrared hand-dorsa vein images. Firstly, the design and realisation of a

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Font, Aragonès Xavier. "Visible, near infrared and thermal hand-based image biometric recognition." Doctoral thesis, Universitat Politècnica de Catalunya, 2013. http://hdl.handle.net/10803/117685.

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Biometric Recognition refers to the automatic identification of a person based on his or her anatomical characteristic or modality (i.e., fingerprint, palmprint, face) or behavioural (i.e., signature) characteristic. It is a fundamental key issue in any process concerned with security, shared resources, network transactions among many others. Arises as a fundamental problem widely known as recognition, and becomes a must step before permission is granted. It is supposed that protects key resources by only allowing those resources to be used by users that have been granted authority to use or t

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Clarke, Fiona Catherine. "Near-infrared microscopy and image analysis for pharmaceutical process control." Thesis, University College London (University of London), 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.432883.

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Karlsson, Jonas. "FPGA-Accelerated Dehazing by Visible and Near-infrared Image Fusion." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-28322.

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Fog and haze can have a dramatic impact on vision systems for land and sea vehicles. The impact of such conditions on infrared images is not as severe as for standard images. By fusing images from two cameras, one ordinary and one near-infrared camera, a complete dehazing system with colour preservation can be achieved. Applying several different algorithms to an image set and evaluating the results, the most suitable image fusion algoritm has been identified. Using an FPGA, a programmable integrated circuit, a crucial part of the algorithm has been implemented. It is capable of producing proc

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Touse, Michael P. "Demonstration of a near and mid-infrared detector using multiple step quantum wells." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03sep%5FTouse.pdf.

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Quartel, John Conrad. "A study of near-field optical imaging using an infrared microscope." Thesis, Imperial College London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313413.

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Books on the topic "Near infrared imagery"

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(Society), SPIE, Optical Society of America, and European Optical Society, eds. Diffuse optical imaging II: 14-17 June 2009, Munich, Germany. SPIE, 2009.

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Hielscher, Andreas H. Diffuse optical imaging III: 22-24 May 2011, Munich, Germany. Edited by SPIE (Society), Optical Society of America, Deutsche Gesellschaft für Lasermedizin, German Biophotonics Research Program, Photonics4Life (Group), and United States. Air Force. Office of Scientific Research. SPIE, 2011.

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The search for extended infrared emission near interacting and active galaxies. National Aeronautics and Space Administration, 1991.

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K, Matthews, and United States. National Aeronautics and Space Administration., eds. The first diffraction-limited images from the W.M. Keck Telescope. National Aeronautics and Space Administration, 1996.

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Book chapters on the topic "Near infrared imagery"

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Ahern, Frank J., Helmut Epp, Donald R. Cahoon, Nancy H. F. French, Eric S. Kasischke, and Jeffery L. Michalek. "Using Visible and Near-Infrared Satellite Imagery to Monitor Boreal Forests." In Ecological Studies. Springer New York, 2000. http://dx.doi.org/10.1007/978-0-387-21629-4_17.

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Carbone, Carlos, Ciro Potena, and Daniele Nardi. "Augmentation of Sunflower-Weed Segmentation Classification with Unity Generated Imagery Including Near Infrared Sensor Data." In Lecture Notes in Networks and Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84811-8_3.

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Li, Stan Z., and Dong Yi. "Face Recognition Using Near Infrared Images." In Handbook of Face Recognition. Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-932-1_15.

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Simons, A. Doug, and B. Eric Becklin. "A Near Diffraction Limited Image of the Galactic Center." In Infrared Astronomy with Arrays. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1070-9_31.

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Testi, L., M. Felli, P. Persia, and M. Roth. "Near infrared images of galactic water masers." In Star Formation and Techniques in Infrared and mm-Wave Astronomy. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58196-0_57.

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Bertin, E. "Classification of Astronomical Images with a Neural Network." In Science with Astronomical Near-Infrared Sky Surveys. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0946-8_11.

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Matsui, Sosuke, Takahiro Okabe, Mihoko Shimano, and Yoichi Sato. "Image Enhancement of Low-Light Scenes with Near-Infrared Flash Images." In Computer Vision – ACCV 2009. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12307-8_20.

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Kang, Jinwoo, David V. Anderson, and Monson H. Hayes. "Direct Image Alignment for Active Near Infrared Image Differencing." In Advanced Concepts for Intelligent Vision Systems. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25903-1_29.

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Taini, Matti, Guoying Zhao, and Matti Pietikäinen. "Weight-Based Facial Expression Recognition from Near-Infrared Video Sequences." In Image Analysis. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02230-2_25.

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Martin, Steven, John Smetanka, Bernard Rauscher, and Mark Hereld. "Near Infrared Images of a Select Sample of Young Stellar Objects in Taurus." In Infrared Astronomy with Arrays. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1070-9_28.

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Conference papers on the topic "Near infrared imagery"

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Suarez, Patricia L., Angel D. Sappa, Boris X. Vintimilla, and Riad I. Hammoud. "Near InfraRed Imagery Colorization." In 2018 25th IEEE International Conference on Image Processing (ICIP). IEEE, 2018. http://dx.doi.org/10.1109/icip.2018.8451413.

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Vertan, Constantin, Corneliu Florea, Laura Florea, and Silviu Badoiu. "On the performance of focus measures in infrared and near-infrared imagery." In 2015 International Symposium on Signals, Circuits and Systems (ISSCS). IEEE, 2015. http://dx.doi.org/10.1109/isscs.2015.7203976.

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Nunez, Abel S., and Michael J. Mendenhall. "Detection of Human Skin in Near Infrared Hyperspectral Imagery." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4779069.

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Ives, Robert W., Hau Ngo, and Stephen Winchell. "Evaluating the information content of near-infrared iris imagery." In the 4th International Symposium. ACM Press, 2011. http://dx.doi.org/10.1145/2093698.2093846.

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Spisz, Thomas S., Jeff C. Taylor, David M. Gibson, et al. "Processing near-infrared imagery of hypersonic space shuttle reentries." In SPIE Defense, Security, and Sensing, edited by Ralph B. Dinwiddie and Morteza Safai. SPIE, 2010. http://dx.doi.org/10.1117/12.849741.

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Pelgrum, H., T. Schmugge, A. Rango, J. Ritchie, and B. Kustas. "Spatial variability of thermal and near infrared imagery in JORNEX." In IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174). IEEE, 1998. http://dx.doi.org/10.1109/igarss.1998.699520.

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Chusseau, Laurent, Pierre Payet, and Jeremy Raoult. "Millimeter wave near-field imagery with micrometer spatial resolution." In 2016 41st International Conference on Infrared, Millimeter, and Terahertz waves (IRMMW-THz). IEEE, 2016. http://dx.doi.org/10.1109/irmmw-thz.2016.7758813.

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Semenishchev, Evgeny A., Viacheslav Voronin, and Aleksandr Zelensky. "Combining images near-infrared and visible data from cameras UAV." In Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV, edited by David W. Messinger and Miguel Velez-Reyes. SPIE, 2019. http://dx.doi.org/10.1117/12.2519538.

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Spisz, Thomas S., Jeff C. Taylor, Stephen W. Kennerly, et al. "Processing ground-based near-infrared imagery of space shuttle re-entries." In SPIE Defense, Security, and Sensing, edited by Douglas Burleigh and Gregory R. Stockton. SPIE, 2012. http://dx.doi.org/10.1117/12.919232.

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Carrión-Ruiz, Berta, and José Luis Lerma. "ANÁLISIS DE COMPONENTES PRINCIPALES DE IMÁGENES MULTIESPECTRALES EN EL ÁMBITO DEL ARTE RUPESTRE." In 1st Congress in Geomatics Engineering. Universitat Politècnica València, 2017. http://dx.doi.org/10.4995/cigeo2017.2017.6597.

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This paper tackles principal component analysis (PCA) in images that include wavelengths between 380-1000 nm. Our approach is focussed on taking advantage of the potencial of ultraviolet and infrarred images, in combination with the visible ones, to improve documentation process and rock art analysis. In this way, we want to improve the discrimination between pigment and support rock, and analyse the spectral behaviour of rock art paintings in the ultraviolet and infrared regions. Three images were used, one image from the ultraviolet (UV) region, one from the visible region (VIS) and another

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Reports on the topic "Near infrared imagery"

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Gould, R. W., Amone Jr., Sydor R. A., Kohler M., Bissett D. D., and W. P. Application of a Near-Infrared Slope Algorithm to Derive Optical Properties From High-Resolution, Hyperspectral Aircraft Imagery. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada432395.

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Becker, Sarah, Megan Maloney, and Andrew Griffin. A multi-biome study of tree cover detection using the Forest Cover Index. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42003.

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Tree cover maps derived from satellite and aerial imagery directly support civil and military operations. However, distinguishing tree cover from other vegetative land covers is an analytical challenge. While the commonly used Normalized Difference Vegetation Index (NDVI) can identify vegetative cover, it does not consistently distinguish between tree and low-stature vegetation. The Forest Cover Index (FCI) algorithm was developed to take the multiplicative product of the red and near infrared bands and apply a threshold to separate tree cover from non-tree cover in multispectral imagery (MSI)

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