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7 July 2020 Endmember and band combined model for hyperspectral unmixing with spectral variability
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Abstract

Spectral variability is one of the most limiting factors in hyperspectral unmixing, so it is important to further study the characteristics of spectral variability to improve the accuracy of unmixing. After conducting simulations under varying irradiation conditions, a linear mixed model combining endmember and band is proposed by introducing a band scaling factor to the endmember scaled spectrum. The total variation constraint is used to smooth the spatial distribution of both endmember and band scaling factors and then alternating iterative optimization is applied to solve the optimization problem. Experiments conducted with both simulated and real hyperspectral data sets indicate that the proposed algorithm is effective in hyperspectral unmixing and is superior to other state-of-the-art algorithms based on spectral variability.

© 2020 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2020/$28.00 © 2020 SPIE
Wuhu Lei, Xuhui Weng, Yong Wang, Sheng Luo, and Xiaodong Ren "Endmember and band combined model for hyperspectral unmixing with spectral variability," Journal of Applied Remote Sensing 14(3), 036505 (7 July 2020). https://doi.org/10.1117/1.JRS.14.036505
Received: 24 December 2019; Accepted: 29 June 2020; Published: 7 July 2020
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