Hyperspectral Unmixing with Gaussian Mixture Model and Low-Rank Representation
نویسندگان
چکیده
منابع مشابه
Hyperspectral Unmixing via Low-Rank Representation with Space Consistency Constraint and Spectral Library Pruning
Spectral unmixing is a popular technique for hyperspectral data interpretation. It focuses on estimating the abundance of pure spectral signature (called as endmembers) in each observed image signature. However, the identification of the endmembers in the original hyperspectral data becomes a challenge due to the lack of pure pixels in the scenes and the difficulty in estimating the number of e...
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Spectral unmixing given a library of endmember spectra can be achieved by multiple endmember spectral mixture analysis (MESMA), which tries to find the optimal combination of endmember spectra for each pixel by iteratively examining each endmember combination. However, as library size grows, computational complexity increases which often necessitates a laborious and heuristic library reduction ...
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2019
ISSN: 2072-4292
DOI: 10.3390/rs11080911