A fast full constraints unmixing method

Zhang Ye; Ran Wei; Qing Yan Wang

doi:10.1117/12.961010

19 October 2012 A fast full constraints unmixing method

Zhang Ye, Ran Wei, Qing Yan Wang

Proceedings Volume 8514, Satellite Data Compression, Communications, and Processing VIII; 85140I (2012) https://doi.org/10.1117/12.961010
Event: SPIE Optical Engineering + Applications, 2012, San Diego, California, United States

Abstract

Mixed pixels are inevitable due to low-spatial resolutions of hyperspectral image (HSI). Linear spectrum mixture model (LSMM) is a classical mathematical model to relate the spectrum of mixing substance to corresponding individual components. The solving of LSMM, namely unmixing, is essentially a linear optimization problem with constraints, which is usually consisting of iterations implemented on decent direction and stopping criterion to terminate algorithms. Such criterion must be properly set in order to balance the accuracy and speed of solution. However, the criterion in existing algorithm is too strict, which maybe lead to convergence rate reducing. In this paper, by broaden constraints in unmixing, a new stopping rule is proposed, which can reduce rate of convergence. The experiments results prove both in runtime and iteration numbers that our method can accelerate convergence processing with only cost of little quality decrease in resulting.

Citation Download Citation

Zhang Ye, Ran Wei, and Qing Yan Wang "A fast full constraints unmixing method", Proc. SPIE 8514, Satellite Data Compression, Communications, and Processing VIII, 85140I (19 October 2012); https://doi.org/10.1117/12.961010

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