Evaluation of speckle noise MAP filtering algorithms applied to SAR images

摘要

This work proposes new speckle reduction filters for multi-look, amplitude-detected Synthetic Aperture Radar (SAR) images based on the maximum a posteriori (MAP) approach and compares their performance. The new filters use an adaptive approach based on the one-dimensional k-means clustering algorithm over the variance ratio and also a region-growing procedure. The trade-off between the loss of radiometric resolution and edge preservation is evaluated in the filtered images. In order to obtain quantitative measures of the speckle reduction and of the edge blurring, we used some parameters such as the classical equivalent number of looks and the Hough transform. Experiments have been carried out with natural images corrupted with synthetic speckle noise following the Rayleigh and square root of gamma distributions and with real SAR images.