Exploiting Sparsity in Remote Sensing for Earth Observation

Sparse signals are commonly expected in Remote Sensing and Earth Observation, yet not fully exploited. We develop sparse reconstruction based algorithms for several problems that cover a wide range of fields including SAR and optical (multispectral and hyperspectral) remote sensing. The developed algorithms are evaluated with both simulated and real remote sensing data, e.g. acquired by spaceborne systems such as TerraSAR-X, TanDEM-X, and WorldView-2 and by airborne sensors such as HyMap and HySpex