A unified sub-pixel mapping model integrating spectral unmixing for hyperspectral imagery

Abstract

Traditional sub-pixel mapping methods were imposed on the fraction image which was generated with spectral unmixing techniques. Obviously, the capability of sub-pixel mapping was limited by the accuracy of the obtained fraction image. In this paper, a unified sub-pixel mapping model was proposed by integrating the spectral unmixing to implement on the low-resolution hyperspectral imagery directly. In this way, the sub-pixel mapping result can be obtained from the original hyperspectral imagery while not the fraction image. The proposed algorithm was tested on the synthetic and real hyperspectral images and experimental results demonstrate that the proposed approach outperform the other three traditional sub-pixel mapping algorithms which was based on the fraction image, and hence provide an effective option for improving the accuracy of sub-pixel mapping of hyperspectral imagery.