Wavelet-based SAR image despeckling using Cauchy pdf modeling

Synthetic Aperture Radar (SAR) is a kind of coherent imaging system that produces a random pattern, named speckle, which degrades the quality of SAR images and affects their further application seriously. Therefore how to restore SAR image from speckled one has become a necessary step in post-processing of image. In this paper, a new despeckling algorithm is presented based on wavelet transform using Cauchy distribution model. First, a new approach based on “second kind statistics” is used to estimate the dispersion parameter of the Cauchy distribution. Then, we apply this Cauchy prior to model the distribution of the wavelet coefficients for the log-transformed reflectance of SAR images and present a new homomorphic wavelet-based maximum a posteriori (MAP) despeckling algorithm in this paper. Finally, the real SAR images are used to verify the proposed algorithm.