Evaluation of SAR-SDNLM filter for change detection classification

This study evaluates the usage of Stochastic Distances Nonlocal Means (SDNLM) speckle filter in an image from Brazilian Amazon. The objective is to evaluate whether the noise reduction improves land cover and change classification. Results obtained from filtered images were compared with those obtained from unfiltered images and images filtered using Gamma Map. Results shows that, when using region based Bhathacharyya Minimum Distance Classifier, land cover and change classification using both speckle filters has accuracy values statistically equal. Analyzing the filtered images themselves, SDNLM obtained better results in terms of visual quality and edges preservation.