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22 May 2014 Fisher's ratio-based criterion for finding endmembers in hyperspectral imagery
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Endmember extraction has recently received considerable interest in hyperspectral imagery. However, several issues in endmember extraction may have been overlooked. The first and foremost is the term of using endmember extraction. Many algorithms claimed to be endmember extraction algorithms actually do not extract true endmembers but rather find potential endmember candidates, referred to as virtual endmembers (VEs). Secondly, how difficult for an algorithm to find VEs is primarily determined by two key factors, endmember variability and endmember discriminability. While the former issue has been addressed recently in the literature, the latter issue is yet explored and has not been investigated before. This paper re-invents a wheel by developing a Fisher’s ratio approach to finding VEs using Fisher’s ratio criterion which is defined by ratio of endmember variability to endmember discriminability.
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Cheng Gao, Shih-Yu Chen, and Chein-I Chang "Fisher's ratio-based criterion for finding endmembers in hyperspectral imagery", Proc. SPIE 9124, Satellite Data Compression, Communications, and Processing X, 91240K (22 May 2014);

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