SAR Image Segmentation Based on Multiscale AutoRegressive and Markov Random Field Models
Liu Ai-ping①②; Fu Kun①; You Hong-jian①; Liu Zhong②
①Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China; ②Electronic Engineering College, Navy Engineering University, Wuhan 430033, China
Abstract:A method of SAR image segmentation based on Multiscale AutoRegressive and Markov Random Field (MAR-MRF) models is presented. MAR models is used to establish mathematic relationship among different image layers, and is combined with Markov Random Field (MRF) segment models. This method takes into account the dependence of neighbor layers Markov property of the same layer, and uses forecasting result of the MAR models to direct the fine layer segmentation. Experimental results on SAR image show that this method reduces the iterative times of segmentation and inaccuracy classify blocks, and gets clear and smooth object border.
刘爱平;付 琨;尤红建;刘 忠. 基于MAR-MRF的SAR图像分割方法[J]. 电子与信息学报, 2009, 31(11): 2556-2562 .
Liu Ai-ping①②; Fu Kun①; You Hong-jian①; Liu Zhong②. SAR Image Segmentation Based on Multiscale AutoRegressive and Markov Random Field Models. , 2009, 31(11): 2556-2562 .