doi:

DOI: 10.3724/SP.J.1146.2009.00512

Journal of Electronics & Information Technology (电子与信息学报) 2010/32:4 PP.925-931

SAR Image Despeckling Based on Local Translation-Rayleigh Distribution Model


Abstract:
Based on the statistical model in stationary wavelet domain, an algorithm of SAR image despeckling is developed. Firstly, nonlogarithmic additive model is applied to SAR image, and then a statistical distribution—Local Translation-Rayleigh Distribution Model (LTRDM) is proposed for the noise within nonlogarithmic additive model in the image domain. Finally, based on this model and in the stationary wavelet domain, the solution of real signal coefficients are given by using Maximum A Posteriori(MAP). Experiments show that local translation-Rayleigh distribution model is effective, and also indicate that a despeckling algorithm based on LTRDM proposed in this paper is robust, and possess high performance over many traditional algorithms.

Key words:SAR image despeckling,Local translation-Rayleigh distribution model,Nonlogarithmic additive model,Stationary wavelet transform,Maximum A Posteriori (MAP)

ReleaseDate:2014-07-21 15:17:52



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