Results 201 to 210 of about 1,373 (228)
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IEEE Transactions on Geoscience and Remote Sensing
Cong Lei, Linfu Xie, Xiaoqiong Qin
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Cong Lei, Linfu Xie, Xiaoqiong Qin
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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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Quantitative assessment of the different methods addressing the endmember variability
2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, 2013Spectral mixture analysis is an important technique to extract desired information from the mixed remotely sensed data. However, current spectral mixture analysis techniques suffered from the endmember variability. Quantitative assessment of SMA techniques with simulated data is critical to understand the influence of endmember variability.
Yuhan Rao +3 more
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Classification Using Unmixing Models in Areas With Substantial Endmember Variability
2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2018Q1
Edurne Ibarrola-Ulzurrun +4 more
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A Gaussian mixture model representation of endmember variability for spectral unmixing
2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2016Endmember variability complicates the problem of spectral unmixing. This variability is typically represented by probability distributions or spectral libraries. The present work describes a new distributional representation based on Gaussian Mixture Models (GMMs).
Yuan Zhou 0004 +2 more
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On the effect of variable endmember spectra in the linear mixture model
IEEE Transactions on Geoscience and Remote Sensing, 2006The linear mixture model is frequently used to characterize surface cover over land, to model the reflectance of heterogeneous surfaces, and, by inversion, to estimate fractional cover from a multispectral satellite signal. It is usually assumed that certain parameters of this model, namely the so-called endmember spectra, are fixed, and that the model
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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 0001 +4 more
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