Restoration of EnMAP Data through Sparse Reconstruction

Abstract

This paper presents the first results of applying sparse reconstruction methods to restore a simulated dataset for the Environmental Mapping and Analysis Program (EnMAP), the forthcoming German spaceborne hyperspectral mission. Each mage element is independently decomposed using contributions from a limited number of pixels, which come directly from the image and have previously undergone a low-pass filtering in noisy bands. Thus, the denoising application is reduced to a weighted sparse unmixing problem. A first assessment of the results is encouraging as the original bands taken into account are reconstructed with a high Signal-to-Noise Ratio and low overall distortions.