A Region Splitting and Hierarchical Unequal Merging Algorithm for Segmentation of Sar Images

In this paper we present an segmentation technique which uses super pixels as the basic unit of operation. The image is first converted into a super pixel image. Then the rules framed by Gestalt based on study of cognitive science are used to extract the features of image such as texture, edges and spatial information. The rule of locality determines the neighboring pixels. The rule of proximity group pixels of same brightness. The rule of consistency is used to identify the boundary for the pixels to be merged. The image is first split using region splitting. Then it is merged in two stages, first abrasively and then finely. In the first stage the pixels within a super pixel are merged and in second stage the pixels along the boundary are merged. The goal of this paper is to obtain segmentation with accuracy. KeywordsSynthetic Aperture Radar, Image Segmentation Region Splitting, Region Merging.