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- W2381069513 abstract "Through defining the new potential functions,a SAR image segmentation method is proposed based on Bayes belief propagation and regional MRF model.Considering the rich texture information of SAR images,texture features are extracted from the watershed over-segmented regions,and then an MRF model is defined over the region adjacency graph of the initially segmented regions.Features of each small region are denoted by the texture features,the average and variance of the gray level of all the pixels in each region.The associated potential function is defined by the initial segmentation obtained from FCM clustering with the region.The features of the small regions are introduced to the interaction potential function.The new interaction potential function can effectively protect edge and promote regional consistency at the same time.In the experiments,the proposed algorithm is compared with other MRF image segmentation algorithms using real SAR images.The experimental results show that the proposed method is more effective for SAR image segmentation." @default.
- W2381069513 created "2016-06-24" @default.
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- W2381069513 date "2010-01-01" @default.
- W2381069513 modified "2023-09-24" @default.
- W2381069513 title "SAR Image Segmentation Using Markov Random Field Based on Regions and Bayes Belief Propagation" @default.
- W2381069513 hasPublicationYear "2010" @default.
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