Speckle reduction and segmentation of Synthetic Aperture Radar images

Two simple modifications to the established sigma filter are proposed, and demonstrated to improve both its efficiency at smoothing speckle noise and its ability to preserve fine features. A fully automatic, unsupervised segmentation algorithm, based on the iterative application of the new filter, is described and successfully applied to ERS-1 Synthetic Aperture Radar (SAR) images of sea ice. The simplicity of this segmentation approach, together with its ability to segment classes separated by a gradual change in grey level intensity, may offer significant advantages over techniques based on edge-detection and region growing.