Speckle noise MAP filtering based on local adaptive neighborhood statistics

This work proposes the use of an adaptive neighborhood procedure to extract local statistical properties of images in order to improve a speckle noise “Maximum a Posteriori” (MAP) filtering performance. The strategy consists in growing the local statistically homogeneous area near the pixel in order to estimate its MAP filtering parameters. Measures evaluating both the signal-to-noise improvement and resolution loss due to filtering are computed. The use of region growing is investigated as a promising approach compared to a fixed size and shape neighborhood