基于半二次型鲁棒高光谱解混框架

Risheng Huang, C. Xia, Shuhan Chen, Liaoying Zhao, Xiaorun Li
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引用次数: 0

摘要

提出了一种通用的半二次型高光谱解调框架来解决鲁棒或稀疏解调问题。通过这个框架可以设计和开发一系列潜在的方法来解决HU问题。通过引入相关熵度量,推导出一种基于相关熵的空间-光谱鲁棒稀疏正则化(CSsRS-NMF)解调方法,同时实现二维鲁棒性和自适应加权稀疏性约束。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Half-quadratic based robust hyperspectral unmixing framework
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.
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