Unmixing Approach for Hyperspectral Data Resolution Enhancement Using High Resolution Multispectral Image with Unknown Spectral Response Function

A novel algorithm based on a Spectral Mixture Analysis (SMA) technique for enhancing the spatial resolution of the hyperspectral (HS) image using high spatial-resolution multispectral (MS) image is described. The proposed algorithm deals with practical remote sensing situation, where the spectral relationship between the observed high spatial-resolution MS image and the estimated high spatial-resolution HS image is unknown. The high-resolution hyperspectral image is reconstructed based on the high-spectral information of low spatial-resolution hyperspectral image represented by endmembers and high-spatial information of high spatial-resolution multispectral image represented by abundances. As a result, a SMA diagram is developed, in which the unmixing process is performed on the MS and HS images sequentially. The spatial spread transform matrix of the sensor observation model is used to produce the matched abundances of the low spatial-resolution HS image, in order to unmix the later. Finally, we utilize a real HYDICE data experiments to show the effectiveness of the proposed fusion algorithm.