A Novel Edge-detection Based Segmentation Algorithm for Polarimetric Sar Images

Aiming at overcoming the disadvantages of the algorithm proposed by White, R. G. (RGW) and making it applicable for PolSAR data classification, a novel edge-detection algorithm based on segmentation for Polarimetric SAR images is proposed in this paper. As one of the famous algorithms based on objected-oriented segmentation, RGW has been used extensively in image segmentation. However, it also has some disadvantages such as a large number of small regions in the segmentation result. In this paper, after a series of pre-processing including edge enhancement and edge detection, the initial segmented small regions are merged according to the region distance defined by distance of coherence matrix of PolSAR data, and discrete points (at the position of edges) are merged into regions according to Wishart distance. We applied the new algorithm to NASA/JPL AIRSAR L band data of Flevoland, Netherlands. Compared with RGW, experiment results demonstrate that the region of Flevoland resulting from our method get superior segment results. In addition, a better classification result is derived from the segmentation result. What’s more, the method has the advantage of edge holding while implementing classification. * Corresponding author: Jie Yang.