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.