Half-quadratic based robust hyperspectral unmixing framework

Risheng Huang; Chaoqun Xia; Shuhan Chen; Liaoying Zhao; Xiaorun Li

doi:10.1117/12.2665465

31 January 2023 Half-quadratic based robust hyperspectral unmixing framework

Risheng Huang, Chaoqun Xia, Shuhan Chen, Liaoying Zhao, Xiaorun Li

Proceedings Volume 12505, Earth and Space: From Infrared to Terahertz (ESIT 2022); 125051G (2023) https://doi.org/10.1117/12.2665465
Event: Earth and Space: From Infrared to Terahertz (ESIT 2022), 2022, Nantong, China

Abstract

We present a general half-quadratic based hyperspectral unmixing (HU) framework to solve the robust or sparse unmixing problem. A series of potential methods can be designed and developed to solve HU problem through this framework. By introducing correntropy metric, a correntropy based spatial-spectral robust sparsity regularized (CSsRS-NMF) unmixing method is derived through the proposed framework to achieve two-dimensional robustness and adaptive weighted sparsity constraint for abundances simultaneously.

Citation Download Citation

Risheng Huang, Chaoqun Xia, Shuhan Chen, Liaoying Zhao, and Xiaorun Li "Half-quadratic based robust hyperspectral unmixing framework", Proc. SPIE 12505, Earth and Space: From Infrared to Terahertz (ESIT 2022), 125051G (31 January 2023); https://doi.org/10.1117/12.2665465

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