Unmixing approach for hyperspectral data resolution enhancement using high resolution multispectral image

Abstract

In order to enhance the spatial resolution of the hyperspectral images, a novel fast algorithm based on Spectral Mixture Analysis (SMA) techniques is proposed for the fusion of coarse-resolution hyperspectral (HS) image and high-resolution multispectral (MS) image. The high-resolution hyperspectral image is synthesized by integrating high-resolution spectral information of hyperspectral image represented by endmembers and high-resolution spatial information of multispectral image represented by abundance. As a result, a novel SMA based diagram is designed, in which Endmember Extraction (EE) is performed on hyperspectral images while Abundance Estimation is performed on multispectral images, and the unmixing process in these two images are matched by utilizing the spectral response matrix and the spatial spread transform matrix in the observation model. Finally, real HYDICE data experiments are utilized to demonstrate the effectiveness of the proposed fusion algorithm.