Fast topology preserving PolSAR image superpixel segmentation
Weiwei Guo, Zenghui Zhang, Juanping Zhao, Wenxian Yu · 2016
In this paper, we propose a fast PolSAR image superpixel segmentation method. This method takes a simple coarse-to-fine optimization technique to minimize a Markov-Random-Field (MRF) like energy function which integrates the Pol- SAR image statistic, spatial position and boundary smoothing. It updates boundary of superpixels staring with a large block level and iterates down to the final pixel level. We demonstrate the performance of our approach both on the synthetic and real full polarimetric images , showing that our proposed approach can achieve significantly faster convergence than SLIC method, and make a good compromise between accuracy and computation speed.