22 May 2014 Endmember variability resolved by pixel purity index in hyperspectral imagery
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Endmember variability presents a great challenge in endmember finding since a true endmember may be contaminated by many unknown factors. This paper develops a pixel purity index (PPI) based approach to resolving this issue. It is known that endmember candidates must have their PPI counts greater than 0. Using this fact we can start with all data samples with PPI counts greater than 0 and cluster them into p endmember classes where the value of p can be determined by virtual dimensionality (VD). We further develop an endmember identification algorithm to select true endmembers from these p endmembers. So, in our proposed technique three state processes are developed. It first uses PPI to produce a set of endmember candidates and then develops a clustering algorithm to group PPI-generated endmember candidates into p endmember classes and finally concludes by designing an algorithm to extract true endmembers from the p endmember classes.
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Yao Li, Yao Li, Cheng Gao, Cheng Gao, Shih-Yu Chen, Shih-Yu Chen, Chein-I Chang, Chein-I Chang, "Endmember variability resolved by pixel purity index in hyperspectral imagery", Proc. SPIE 9124, Satellite Data Compression, Communications, and Processing X, 91240I (22 May 2014); doi: 10.1117/12.2049034; https://doi.org/10.1117/12.2049034

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