A Multiscale Hierarchical Model for Sparse Hyperspectral Unmixing
نویسندگان
چکیده
منابع مشابه
Sparse Hyperspectral Unmixing
Given a set of mixed spectral vectors, spectral mixture analysis (or spectral unmixing) aims at estimating the number of reference materials, also called endmembers, their spectral signatures, and their fractional abundances. A semi-supervised approach to deal with the linear spectral unmixing problem consists in assuming that the observed spectral vectors are linear combinations of a small num...
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Hyperspectral Unmixing (HU) has received increasing attention in the past decades due to its ability of unveiling information latent in hyperspectral data. Unfortunately, most existing methods fail to take advantage of the spatial information in data. To overcome this limitation, we propose a Structured Sparse regularized Nonnegative Matrix Factorization (SS-NMF) method from the following two a...
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Spectral unmixing is an important problem in hyperspectral data exploitation. It amounts at characterizing the mixed spectral signatures collected by an imaging instrument in the form of a combination of pure spectral constituents (endmembers), weighted by their correspondent abundance fractions. Linear spectral unmixing is a popular technique in the literature which assumes linear interactions...
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Sparse hyperspectral unmixing from large spectral libraries has been considered to circumvent limitations of endmember extraction algorithms in many applications. This strategy often leads to ill-posed inverse problems, which can benefit from spatial regularization strategies. While existing spatial regularization methods improve the problem conditioning and promote piecewise smooth solutions, ...
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Chang Li 1, Yong Ma 2,∗, Xiaoguang Mei 2, Chengyin Liu 1 and Jiayi Ma 2 1 School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China; [email protected] (C.L.); [email protected] (C.L.) 2 Electronic Information School, Wuhan University, Wuhan 430072, China; [email protected] (X.M.); [email protected] (J.M.) * Corresponden...
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2019
ISSN: 2072-4292
DOI: 10.3390/rs11050500