2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)
DOI: 10.1109/whispers.2015.8075400
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In this paper we apply the Multi-Look Joint Sparsity Fusion algorithm to multisensor image data. Our algorithm at first performs sparse unmixing of the hyperspectral data and selects pixels for a second unmixing of the multispectral image. This is done by applying a joint sparsity model, which exploits similarities within neighbouring pixels. We test our resolution enhancement method using a hyperspectral and a multispectral image with a spatial resolution of 30 m and 3 m, respectively. To asses the results we evaluate the classification result of the resolution enhanced and original images.