Sparse Signal Representation for Complex-Valued Imaging
Sadegh Samadi, Müjdat Çetin, Mohammad Ali Masnadi-Shirazi
IEEE Signal Processing Society 13th DSP Workshop & 5th SPE Workshop, Marco Island, Florida, USA, January 2009
Abstract: We propose a sparse signal representation-based method for complexvalued imaging. Many coherent imaging systems such as synthetic aperture radar (SAR) have an inherent random phase, complexvalued nature. On the other hand sparse signal representation, which has mostly been exploited in real-valued problems, has many capabilities such as superresolution and feature enhancement for various reconstruction and recognition tasks. For complex-valued problems, the key challenge is how to choose the dictionary and the representation scheme for effective sparse representation. We propose a mathematical framework and an associated optimization algorithm for a sparse signal representation-based imaging method that can deal with these issues. Simulation results show that this method offers improved results compared to existing powerful imaging techniques.