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This paper presents a new strategy in order to accelerate the execution of sequential endmember extraction algorithms without compromising their performance in terms of the accuracy of the estimated endmembers. In particular, our proposal takes advantage of the correlation between pixels located in adjacent spatial positions as well as of the information provided by the dimensionality reduction step...
Endmember extraction represents one of the most challenging aspects of hyperspectral image processing. In this letter, a new algorithm for endmember extraction, named modified vertex component analysis (MVCA), is presented. This new technique outperforms the popular vertex component analysis (VCA) by applying a low-complexity orthogonalization method and by utilizing integer instead of floating-point...
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