Littérature scientifique sur le sujet « HYPER/MULTISPECTRAL IMAGERY »
Créez une référence correcte selon les styles APA, MLA, Chicago, Harvard et plusieurs autres
Sommaire
Consultez les listes thématiques d’articles de revues, de livres, de thèses, de rapports de conférences et d’autres sources académiques sur le sujet « HYPER/MULTISPECTRAL IMAGERY ».
À côté de chaque source dans la liste de références il y a un bouton « Ajouter à la bibliographie ». Cliquez sur ce bouton, et nous générerons automatiquement la référence bibliographique pour la source choisie selon votre style de citation préféré : APA, MLA, Harvard, Vancouver, Chicago, etc.
Vous pouvez aussi télécharger le texte intégral de la publication scolaire au format pdf et consulter son résumé en ligne lorsque ces informations sont inclues dans les métadonnées.
Articles de revues sur le sujet "HYPER/MULTISPECTRAL IMAGERY"
Undrajavarapu, Jemima, et M. Chandra Sekhar. « Hyper Spectral Remote Sensing for Mapping Species and Characteristics of Mangroves in Krishna Delta Region ». Current World Environment 15, no 3 (30 décembre 2020) : 613–18. http://dx.doi.org/10.12944/cwe.15.3.25.
Texte intégralHu, Ting, Hongyan Zhang, Huanfeng Shen et Liangpei Zhang. « Robust Registration by Rank Minimization for Multiangle Hyper/Multispectral Remotely Sensed Imagery ». IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7, no 6 (juin 2014) : 2443–57. http://dx.doi.org/10.1109/jstars.2014.2311585.
Texte intégralZhou, Jing, Biwen Wang, Jiahao Fan, Yuchi Ma, Yi Wang et Zhou Zhang. « A Systematic Study of Estimating Potato N Concentrations Using UAV-Based Hyper- and Multi-Spectral Imagery ». Agronomy 12, no 10 (17 octobre 2022) : 2533. http://dx.doi.org/10.3390/agronomy12102533.
Texte intégralChen Shan-Jing, Hu Yi-Hua, Sun Du-Juan et Xu Shi-Long. « A simulation method by air and space integrated fusion based on hyper-/multispectral imagery ». Acta Physica Sinica 62, no 20 (2013) : 204201. http://dx.doi.org/10.7498/aps.62.204201.
Texte intégralSharif, I., et S. Khare. « Comparative Analysis of Haar and Daubechies Wavelet for Hyper Spectral Image Classification ». ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (28 novembre 2014) : 937–41. http://dx.doi.org/10.5194/isprsarchives-xl-8-937-2014.
Texte intégralOlivetti, Diogo, Rejane Cicerelli, Jean-Michel Martinez, Tati Almeida, Raphael Casari, Henrique Borges et Henrique Roig. « Comparing Unmanned Aerial Multispectral and Hyperspectral Imagery for Harmful Algal Bloom Monitoring in Artificial Ponds Used for Fish Farming ». Drones 7, no 7 (21 juin 2023) : 410. http://dx.doi.org/10.3390/drones7070410.
Texte intégralHonkavaara, E., R. Näsi, R. Oliveira, N. Viljanen, J. Suomalainen, E. Khoramshahi, T. Hakala et al. « USING MULTITEMPORAL HYPER- AND MULTISPECTRAL UAV IMAGING FOR DETECTING BARK BEETLE INFESTATION ON NORWAY SPRUCE ». ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (21 août 2020) : 429–34. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-429-2020.
Texte intégralDWIJESH H P, JAYANTH, SANDEEP S. V et RASHMI S. « Computerized or Automated Object Recognition and Analysis of Pattern Matching in Runways Using Surface Track Data ». Journal of University of Shanghai for Science and Technology 23, no 11 (6 novembre 2021) : 159–65. http://dx.doi.org/10.51201/jusst/21/10867.
Texte intégralPham, Tien Dat, Junshi Xia, Nam Thang Ha, Dieu Tien Bui, Nga Nhu Le et Wataru Tekeuchi. « A Review of Remote Sensing Approaches for Monitoring Blue Carbon Ecosystems : Mangroves, Seagrassesand Salt Marshes during 2010–2018 ». Sensors 19, no 8 (24 avril 2019) : 1933. http://dx.doi.org/10.3390/s19081933.
Texte intégralPereira-Sandoval, Marcela, Ana Ruescas, Patricia Urrego, Antonio Ruiz-Verdú, Jesús Delegido, Carolina Tenjo, Xavier Soria-Perpinyà, Eduardo Vicente, Juan Soria et José Moreno. « Evaluation of Atmospheric Correction Algorithms over Spanish Inland Waters for Sentinel-2 Multi Spectral Imagery Data ». Remote Sensing 11, no 12 (21 juin 2019) : 1469. http://dx.doi.org/10.3390/rs11121469.
Texte intégralThèses sur le sujet "HYPER/MULTISPECTRAL IMAGERY"
Carmody, James Daniel Physical Environmental & Mathematical Sciences Australian Defence Force Academy UNSW. « Deriving bathymetry from multispectral and hyperspectral imagery ». Awarded by:University of New South Wales - Australian Defence Force Academy. School of Physical, Environmental and Mathematical Sciences, 2007. http://handle.unsw.edu.au/1959.4/38654.
Texte intégralMartínez, Usó Adolfo. « Unsupervised Band Selection and Segmentation in Hyper/Multispectral Images ». Doctoral thesis, Universitat Jaume I, 2008. http://hdl.handle.net/10803/10483.
Texte intégralSecondly, the problem of segmentation strictly speaking is still a challenging question whatever the input image would be.
This thesis is focused on solving the whole process by means of building an image processing method that analyses and optimises the information acquired by a multispectral device. After that, it detects the main regions that are present in the scene in an image segmentation procedure. Therefore, this work will be divided into two parts. In the first part, an approach for selecting the most relevant subset of input bands will be presented. In the second part, this reduced representation of the initial bands will be the input data of a segmentation method.
Finally, the main contributions of this PhD work could be briefly summarised as follows. On the one hand, we have proposed a pre-processing stage with an unsupervised band selection approach based on information measures that reduces considerably the amount of data. This approach has been successfully compared with well-known algorithms of the literature, showing its good performance with regard to pixel image classification tasks. On the other hand, after the band selection stage, two unsupervised segmentation procedures for detecting the main parts in multispectral images have been also developed. Regarding to this segmentation part, we have mainly contributed with two measures of similarity among regions. An objective functional for selecting an optimal (or close to optimal) partition of the image is another relevant contribution too.
Benhalouche, Fatima Zohra. « Méthodes de démélange et de fusion des images multispectrales et hyperspectrales de télédétection spatiale ». Thesis, Toulouse 3, 2018. http://www.theses.fr/2018TOU30083/document.
Texte intégralIn this thesis, we focused on two main problems of the spatial remote sensing of urban environments which are: "spectral unmixing" and "fusion". In the first part of the thesis, we are interested in the spectral unmixing of hyperspectral images of urban scenes. The developed methods are designed to unsupervisely extract the spectra of materials contained in an imaged scene. Most often, spectral unmixing methods (methods known as blind source separation) are based on the linear mixing model. However, when facing non-flat landscape, as in the case of urban areas, the linear mixing model is not valid any more, and must be replaced by a nonlinear mixing model. This nonlinear model can be reduced to a linear-quadratic/bilinear mixing model. The proposed spectral unmixing methods are based on matrix factorization with non-negativity constraint, and are designed for urban scenes. The proposed methods generally give better performance than the tested literature methods. The second part of this thesis is devoted to the implementation of methods that allow the fusion of multispectral and hyperspectral images, in order to improve the spatial resolution of the hyperspectral image. This fusion consists in combining the high spatial resolution of multispectral images and high spectral resolution of hyperspectral images. The implemented methods are designed for urban remote sensing data. These methods are based on linear-quadratic spectral unmixing techniques and use the non-negative matrix factorization. The obtained results show that the developed methods give good performance for hyperspectral and multispectral data fusion. They also show that these methods significantly outperform the tested literature approaches
PATEL, RISHI. « MATERIAL CLASS MAPPING BY REFLECTANCE MATCHING OF HYPER/MULTISPECTRAL IMAGERY ». Thesis, 2017. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16037.
Texte intégralLivres sur le sujet "HYPER/MULTISPECTRAL IMAGERY"
Jia, Xiuping. Field Guide to Hyper/Multispectral Image Processing. SPIE, 2022.
Trouver le texte intégralChapitres de livres sur le sujet "HYPER/MULTISPECTRAL IMAGERY"
Kozma-Bognár, Veronika, et József Berke. « Determination of Optimal Hyper- and Multispectral Image Channels by Spectral Fractal Structure ». Dans Lecture Notes in Electrical Engineering, 255–62. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06773-5_34.
Texte intégralActes de conférences sur le sujet "HYPER/MULTISPECTRAL IMAGERY"
Dian, Yuanyong, Zengyuan Li et Yong Pang. « Forest tree species clssification based on airborne hyper-spectral imagery ». Dans Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, sous la direction de Jinwen Tian et Jie Ma. SPIE, 2013. http://dx.doi.org/10.1117/12.2030554.
Texte intégralBernstein, L. S., S. M. Adler-Golden, R. L. Sundberg et A. J. Ratkowski. « Improved reflectance retrieval from hyper- and multispectral imagery without prior scene or sensor information ». Dans Remote Sensing, sous la direction de James R. Slusser, Klaus Schäfer et Adolfo Comerón. SPIE, 2006. http://dx.doi.org/10.1117/12.705038.
Texte intégralPerkins, Timothy, Steven Adler-Golden, Michael Matthew, Alexander Berk, Gail Anderson, James Gardner et Gerald Felde. « Retrieval of atmospheric properties from hyper and multispectral imagery with the FLAASH atmospheric correction algorithm ». Dans Remote Sensing, sous la direction de Klaus Schäfer, Adolfo Comerón, James R. Slusser, Richard H. Picard, Michel R. Carleer et Nicolaos I. Sifakis. SPIE, 2005. http://dx.doi.org/10.1117/12.626526.
Texte intégralConant, John A., et Kurt D. Annen. « Automated hyper/multispectral image analysis tool ». Dans Aerospace/Defense Sensing, Simulation, and Controls, sous la direction de Sylvia S. Shen et Michael R. Descour. SPIE, 2001. http://dx.doi.org/10.1117/12.437003.
Texte intégralMehta, Sanjeev, Kuhelika Bera et R. M. Parmar. « Camera electronics for hyper-spectral imager ». Dans Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications II. SPIE, 2008. http://dx.doi.org/10.1117/12.806225.
Texte intégralAiazzi, Bruno, Luciano Alparone, Alberto Arienzo, Andrea Garzelli et Simone Lolli. « Fast multispectral pansharpening based on a hyper-ellipsoidal color space ». Dans Image and Signal Processing for Remote Sensing XXV, sous la direction de Lorenzo Bruzzone, Francesca Bovolo et Jon Atli Benediktsson. SPIE, 2019. http://dx.doi.org/10.1117/12.2533481.
Texte intégralGuérineau, Nicolas, Guillaume Druart, Frédéric Gillard, Yann Ferrec, Mathieu Chambon, Sylvain Rommeluère, Grégory Vincent, Riad Haïdar, Jean Taboury et Manuel Fendler. « Compact designs of hyper- or multispectral imagers compatible with the detector dewar ». Dans SPIE Defense, Security, and Sensing, sous la direction de Bjørn F. Andresen, Gabor F. Fulop et Paul R. Norton. SPIE, 2011. http://dx.doi.org/10.1117/12.883904.
Texte intégralLin, Yu, Ningfang Liao, Xinquan Wang, Deqi Cui, Minyong Liang et Yongdao Luo. « Simultaneous acquisition of hyper-spectral image using the computed tomography imaging interferometer ». Dans International Symposium on Multispectral Image Processing and Pattern Recognition, sous la direction de Tianxu Zhang, Carl A. Nardell, Duane D. Smith et Hangqing Lu. SPIE, 2007. http://dx.doi.org/10.1117/12.750221.
Texte intégralSong, Rui, Shengping Xia et Jianjun Liu. « RSOM tree and class specific hyper graph based distributed image retrieval ». Dans Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, sous la direction de Jianguo Liu, Kunio Doi, Aaron Fenster et S. C. Chan. SPIE, 2009. http://dx.doi.org/10.1117/12.832355.
Texte intégralGilchrist, John R., Christopher Durell et Torbjorn Skauli. « IEEE P4001 : progress update towards an international standard for push-broom hyper-spectral imagers ». Dans Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVII, sous la direction de David W. Messinger et Miguel Velez-Reyes. SPIE, 2021. http://dx.doi.org/10.1117/12.2588466.
Texte intégralRapports d'organisations sur le sujet "HYPER/MULTISPECTRAL IMAGERY"
Burks, Thomas F., Victor Alchanatis et Warren Dixon. Enhancement of Sensing Technologies for Selective Tree Fruit Identification and Targeting in Robotic Harvesting Systems. United States Department of Agriculture, octobre 2009. http://dx.doi.org/10.32747/2009.7591739.bard.
Texte intégral