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.