ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-7, 119-124, 2016
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-7/119/2016/
doi:10.5194/isprs-annals-III-7-119-2016
 
07 Jun 2016
SAR IMAGE SEGMENTATION WITH UNKNOWN NUMBER OF CLASSES COMBINED VORONOI TESSELLATION AND RJMCMC ALGORITHM
Q. H. Zhao, Y. Li, and Y. Wang Institute for Remote Sensing Science and Application, School of Geomatics, Liaoning Technical University, Fuxin, Liaoning 123000, China
Keywords: SAR, segmentation, Bayesian paradigm, unknown number of classes, Voronoi tessellation, RJMCMC Abstract. This paper presents a novel segmentation method for automatically determining the number of classes in Synthetic Aperture Radar (SAR) images by combining Voronoi tessellation and Reversible Jump Markov Chain Monte Carlo (RJMCMC) strategy. Instead of giving the number of classes a priori, it is considered as a random variable and subject to a Poisson distribution. Based on Voronoi tessellation, the image is divided into homogeneous polygons. By Bayesian paradigm, a posterior distribution which characterizes the segmentation and model parameters conditional on a given SAR image can be obtained up to a normalizing constant; Then, a Revisable Jump Markov Chain Monte Carlo(RJMCMC) algorithm involving six move types is designed to simulate the posterior distribution, the move types including: splitting or merging real classes, updating parameter vector, updating label field, moving positions of generating points, birth or death of generating points and birth or death of an empty class. Experimental results with real and simulated SAR images demonstrate that the proposed method can determine the number of classes automatically and segment homogeneous regions well.
Conference paper (PDF, 811 KB)


Citation: Zhao, Q. H., Li, Y., and Wang, Y.: SAR IMAGE SEGMENTATION WITH UNKNOWN NUMBER OF CLASSES COMBINED VORONOI TESSELLATION AND RJMCMC ALGORITHM, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-7, 119-124, doi:10.5194/isprs-annals-III-7-119-2016, 2016.

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