Bayesian TV denoising of SAR images
Miguel Vega, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos · 2011
Synthetic aperture radar (SAR) imagery suffers from the speckle phenomenon. Speckle gives rise to the presence of multiplicative noise which severely degrades the observed images. It is known that logarithmically transformed speckle can be well approximated by a Gaussian distribution. In this paper we propose an algorithm for despeckling images, within the log-transformed spatial domain, using a TV prior whose model parameter is automatically determined using the Evidence Analysis within the Hierarchical Bayesian Paradigm. The effectiveness of the proposed algorithm, over both synthetically speckled and real SAR images, is studied.