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Using High-Resolution Airborne and Satellite Imagery to Assess Crop Growth and Yield Variability for Precision Agriculture
2013
Proceedings of the IEEE
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Image processing techniques including vegetation indices, unsupervised classification, correlation and regression analysis, principal component analysis, and supervised and unsupervised linear spectral ...
In this paper, an overview is given on the use of airborne multispectral and hyperspectral imagery and high-resolution satellite imagery for assessing crop growth and yield variability. ...
Gomez of USDA-ARS, Weslaco, TX, for acquiring the airborne imagery; W. Swanson and J. Forward of USDA-ARS, Weslaco, TX, for ground data collection and image rectification; and D. Murden, M. ...
doi:10.1109/jproc.2012.2196249
fatcat:gho4kovl55awpfuzdzhchjix2m
Front Matter: Volume 9874
2016
Remotely Sensed Data Compression, Communications, and Processing XII
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The publisher is not responsible for the validity of the information or for any outcomes resulting from reliance thereon. ...
Please use the following format to cite material from these proceedings: Publication of record for individual papers is online in the SPIE Digital Library. ...
hyperspectral imagery 9874 0T Separate texture and structure processing for image compression 9874 0Z A nonlinear spectral unmixing method for abundance retrieval of mineral mixtures 9874 10 Real-time ...
doi:10.1117/12.2246638
fatcat:67cih5mf6vb6thriylnoqdar3a
A preliminary approach on the use of satellite hyperspectral data for geological mapping
2007
Bulletin of the Geological Society of Greece
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The noisiest bands were removed and sixty bands were selected for further processing. ...
Further processing of the data has to be done using the image analysis algorithms that have been developed specifically to exploit the extensive information contained in hyperspectral imagery. ...
As a result of the optical control only 152 bands were used for further processing. ...
doi:10.12681/bgsg.17251
fatcat:pxvuzjcepravnlcslvxzxskkym
Estimating the coverage of coral reef benthic communities from airborne hyperspectral remote sensing data: multiple discriminant function analysis and linear spectral unmixing
2011
International Journal of Remote Sensing
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Dr Tom Spencer at the University of Cambridge is thanked for guidance on the manuscript and Dr Rainer Reuter, University of Oldenburg, is thanked for assistance with fieldwork. ...
Acknowledgements This work would not have been possible without the generous support of the Khaled bin Sultan Living Oceans Foundation. ...
Hamylton The success of this unmixing approach implies promise for users of hyperspectral imagery to employ coarser spatial resolution imagery for underwater applications. ...
doi:10.1080/01431161.2011.574162
fatcat:tl6gtph66rd3nj4whniddfwhgq
A Parallel Unmixing-Based Content Retrieval System for Distributed Hyperspectral Imagery Repository on Cloud Computing Platforms
2021
Remote Sensing
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This paper proposes a novel parallel CBIR system for hyperspectral image (HSI) repository on cloud computing platforms under the guide of unmixed spectral information, i.e., endmembers and their associated ...
To address this limitation, we implement a distributed and parallel unmixing method that operates on cloud computing platforms in parallel for accelerating the unmixing processing flow. ...
Acknowledgments: We are grateful to United States Geological Survey (USGS), who provided the spectral library for this research. ...
doi:10.3390/rs13020176
fatcat:7b5xofj425dtxboklearf4ojym
An Improved Nonlocal Sparse Unmixing Algorithm for Hyperspectral Imagery
2015
IEEE Geoscience and Remote Sensing Letters
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As a result of the spatial consideration of the imagery, spatial sparse unmixing (SU) can improve the unmixing accuracy for hyperspectral imagery, based on the application of a spectral library and sparse ...
Index Terms-Hyperspectral imagery, nonlocal, sparse unmixing (SU), spatial information, weight calculation. ...
Plaza for sharing their algorithms for comparison purposes together with the AVIRIS data. They also thank the reviewers for their helpful comments. ...
doi:10.1109/lgrs.2014.2367028
fatcat:uowcllgk7rdg7otyabeqn56c4y
Optical characterization of two cyanobacteria genera, Aphanizomenon and Microcystis, with hyperspectral microscopy
2018
Journal of Applied Remote Sensing
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Blooms of Microcystis, for example, may consist of strains of microcystin-producing and nonmicrocystin-producing cells distinguishable only by laboratory analysis of gene expression. 2 Higher nutrient ...
Optical characterization of two cyanobacteria genera, Aphanizomenon and Microcystis, with hyperspectral microscopy," Abstract. ...
We acknowledge Eric Tvinnereim for his work in the field at Upper Klamath Lake. A brief description of these results was published in Ref. 17 . ...
doi:10.1117/1.jrs.12.036013
fatcat:neoz5vsj2baehacfdgvdutindq
Progress in Hyperspectral Remote Sensing Science and Technology in China Over the Past Three Decades
2014
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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This paper reviews progress in hyperspectral remote sensing (HRS) in China, focusing on the past three decades. ...
These tools such as the Hyperspectral Image Processing and Analysis System (HIPAS) incorporate a number of special algorithms and features designed to take advantage of the wealth of information contained ...
Like the NMM, the main tasks for linear spectral unmixing include endmember determination and abundance estimation. ...
doi:10.1109/jstars.2013.2267204
fatcat:yu4pp5zyqzhafa4ec7m3vva7xi
Nonnegative matrix factorization for hyperspectral unmixing using prior knowledge of spectral signatures
2012
Optical Engineering: The Journal of SPIE
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Hyperspectral unmixing is a process aiming at identifying the constituent materials and estimating the corresponding fractions from hyperspectral imagery of a scene. ...
Non-negative matrix factorization (NMF), an effective linear spectral mixture model, has been applied in hyperspectral unmixing during recent years. ...
NMF for Hyperspectral Unmixing In this section, we first briefly introduce the linear mixing model, which is the most widely used model in spectral unmixing. ...
doi:10.1117/1.oe.51.8.087001
fatcat:thigvb7rvfedhnvxckyvswbyue
Front Matter: Volume 6966
2008
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV
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Publication of record for individual papers is online in the SPIE Digital Library. ...
Downloaded From: https://www.spiedigitallibrary.org/conference-proceedings-of-spie on 7/19/2018 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use ...
(United Kingdom) SPECTRAL UNMIXING 6966 1B A generalized linear mixing model for hyperspectral imagery [6966-46] D. Gillis, J. Bowles, Naval Research Lab. (USA); E. J. Ientilucci, D. W. ...
doi:10.1117/12.801998
fatcat:rt2tub26ezcavdqt6uztn4g3hm
Rolling Guidance Based Scale-Aware Spatial Sparse Unmixing for Hyperspectral Remote Sensing Imagery
2017
Remote Sensing
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Hence, the spatial sparse unmixing methods should be a worthwhile approach for hyperspectral remote sensing image processing. ...
and recover the different levels of important structures and details in the hyperspectral remote sensing image unmixing procedure, as the different levels of structures and edges in remote sensing imagery ...
Ma for sharing their latest sparse unmixing algorithm source code and their good suggestions as to how we could improve our paper. ...
doi:10.3390/rs9121218
fatcat:no56rbuypnfztdi6qrdlnqrcra
Joint Local Block Grouping with Noise-Adjusted Principal Component Analysis for Hyperspectral Remote-Sensing Imagery Sparse Unmixing
2019
Remote Sensing
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To obtain a more reliable and efficient spatial regularized sparse unmixing results, a joint local block grouping with noise-adjusted principal component analysis for hyperspectral remote-sensing imagery ...
unmixing model in the form of sparse regression. ...
Plaza for sharing the simulated datasets and the source code of the latest sparse algorithms with the community, together with the free downloads of the AVIRIS image. ...
doi:10.3390/rs11101223
fatcat:dlabi4bo4fephn3w45ie2adpe4
Editorial for the Special Issue: Multispectral and Hyperspectral Remote Sensing Data for Mineral Exploration and Environmental Monitoring of Mined Areas
2021
Remote Sensing
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In recent decades, multispectral and hyperspectral remote sensing data provide unprecedented opportunities for the initial stages of mineral exploration and environmental hazard monitoring [...] ...
We wish to extend our sincere gratitude to Quenby Qu (assistant editor) and MDPI editorial team for supporting the guest editors in efficiently processing each manuscript. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs13030519
fatcat:k2xtcft5ozdejcxwtis6npcuju
Spectral imaging applications: remote sensing, environmental monitoring, medicine, military operations, factory automation, and manufacturing
1997
25th AIPR Workshop: Emerging Applications of Computer Vision
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Spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. ...
Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. ...
based on the same two scanning techniques for hyperspectral imagery]. ...
doi:10.1117/12.267840
fatcat:7457j4ghovabjpkxfmzswur6wy
Fusion of Various Band Selection Methods for Hyperspectral Imagery
2019
Remote Sensing
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Two versions of BSF, called progressive BSF and simultaneous BSF, are developed for this purpose. ...
This paper presents an approach to band selection fusion (BSF) which fuses bands produced by a set of different band selection (BS) methods for a given number of bands to be selected, nBS. ...
Linear Spectral Unmixing HYDICE data was first used for linear spectral unmixing. Detailed information of HYDICE data is described in Appendix A.1. ...
doi:10.3390/rs11182125
fatcat:hx6rd5fo45b2jco37njqq5zjgi
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