Kriti Mahajan1, Urvashi Garg1, Nitin Mittal2, Yunyoung Nam3, Byeong-Gwon Kang4,*, Mohamed Abouhawwash5,6
CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3705-3720, 2022, DOI:10.32604/cmc.2022.027936
Abstract Spectral unmixing is essential for exploitation of remotely sensed data of Hyperspectral Images (HSI). It amounts to the identification of a position of spectral signatures that are pure and therefore called end members and their matching fractional, draft rules abundances for every pixel in HSI. This paper aims to unmix hyperspectral data using the minimal volume method of elementary scrutiny. Moreover, the problem of optimization is solved by the implementation of the sequence of small problems that are constrained quadratically. The hard constraint in the final step for the abundance fraction is then replaced with a loss function of hinge… More >
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