A Restoration Model Based Despeckling Algorithm of High Resolution SAR Images
一种基于退化模型的高分辨率SAR去噪算法

In order to preserve the textural feature affected by multiplicative speckle especially in high resolution synthetic aperture radar(SAR) images,this paper proposes a despeckling method based on the Gauss-Markov model to suppress the speckle in SAR images.By introducing bayesian analysis framework,restoration model of degradation image of markov random field is built,and then the problem of image restoration is transformed into the problem of solving a maximum a posterior(MAP),random field model parameters can be also estimated directly from noise image,thus speckle is effectively reduced.In this paper,on the basis of discussing the main idea of the restoration model based despeckling(RMBD) algorithm in detail,other commonly used denoising methods are compared with the proposed method,experiments show that the model-based despeckling algorithm achieves better performance not only at speckle reduction but also at preservation of structural detail information than other commonly used speckle filters.