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Endmember orthonormal mapping in hyperspectral mixture analysis to address endmember variability
Earth Science Informatics, 2016Spectral unmixing estimates the abundance of each endmember at every pixel of a hyperspectral image. Each material in traditional unmixing algorithms is represented through a constant spectral signature. However, endmember variability always exists due to environmental, atmospheric, and temporal conditions, which leads to poor accuracy of the estimated
Mohammad Mehdi Ebadzadeh +2 more
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Endmember variability in Spectral Mixture Analysis: A review
Remote Sensing of Environment, 2011The composite nature of remotely sensed spectral information often masks diagnostic spectral features and hampers the detailed identification and mapping of targeted constituents of the earth's surface. Spectral Mixture Analysis (SMA) is a well established and effective technique to address this mixture problem.
Gregory P Asner +2 more
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IEEE Signal Processing Magazine, 2014
Variable illumination and environmental, atmospheric, and temporal conditions cause the measured spectral signature for a material to vary within hyperspectral imagery. By ignoring these variations, errors are introduced and propagated throughout hyperspectral image analysis.
Alina Zare, K C Ho
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Variable illumination and environmental, atmospheric, and temporal conditions cause the measured spectral signature for a material to vary within hyperspectral imagery. By ignoring these variations, errors are introduced and propagated throughout hyperspectral image analysis.
Alina Zare, K C Ho
exaly +3 more sources
Archetypal analysis for endmember bundle extraction considering spectral variability
2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2018With the development of imaging technology, remote sensing images with a high spatial and spectral resolution have become available and have been used in various applications. Although many endmember extraction algorithms have been proposed for hyperspectral data sets which extract/select the standard endmember spectrum for each existing endmember ...
Mingming Xu
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Probabilistic Generative Model for Hyperspectral Unmixing Accounting for Endmember Variability
IEEE Transactions on Geoscience and Remote Sensing, 2022 The complex nature of hyperspectral images makes the analysis of spectral signatures a challenging task in remote sensing. For quantitative analysis, spectral unmixing is a well-established and effective tool to analyze the spectra and spatial ...
Shuaikai Shi +4 more
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Variational Autoencoders for Hyperspectral Unmixing with Endmember Variability
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021Spectral signatures are usually affected by variations in environmental conditions. The spectral variability is thus one of the most important and challenging problems to be addressed in hyperspectral unmixing. Generally, it is a non-trivial task to model the endmember variability, and existing spectral unmixing methods that address the spectral ...
Shuaikai Shi +3 more
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IEEE Transactions on Geoscience and Remote Sensing, 2000
Accuracy of vegetation cover fractions, computed with spectral mixture analysis, may be compromised by variation in canopy structure and biochemistry when a single endmember represents top-of-canopy reflectance. In this article, endmember variability is incorporated into mixture analysis by representing each endmember by a set or bundle of spectra ...
C. Ann Bateson +2 more
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Accuracy of vegetation cover fractions, computed with spectral mixture analysis, may be compromised by variation in canopy structure and biochemistry when a single endmember represents top-of-canopy reflectance. In this article, endmember variability is incorporated into mixture analysis by representing each endmember by a set or bundle of spectra ...
C. Ann Bateson +2 more
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Alternating angle minimization based unmixingwith endmember variability
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016Several techniques exist for dealing with spectral variability in hyperspectral unmixing, such as multiple endmember spectral mixture analysis (MESMA) or compositional models. These algorithms are computationally very involved, and often cannot be executed on problems of reasonable size. In this work, we present a new algorithm for solving the unmixing
Rob Heylen +3 more
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Variability of the endmembers in spectral unmixing
2019Spectral unmixing is an inverse problem in hyperspectral imaging that aims at recovering the spectra of the pure constituents of an image (called endmembers), as well as at estimating the proportions of said materials in each pixel (called abundances).
Drumetz, Lucas +2 more
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