Second Generation Bandelet-Domain Hidden Markov Tree-3S Model For SAR Image Segmentation

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    Since the segmentation results of SAR images by traditional transform domain hidden Markov Tree (HMT) Model were unsatisfactory in homogenous regions and exact edges, a new segmentation method based on second generation bandelet-domain HMT-3S model was proposed . The method was called BHMT-3Sseg shortly. HMT-3S is a special kind of HMT which combines the correlation of different subbands. It is more reasonable to characterize texture regions than HMT model. BHMT-3Sseg models the second generation Bandelet coefficients of an image by using HMT-3S, and the SAR image segmentation results were obtained by training the parameters of HMT-3S and computing the likelihood of each scale and multiscale fusion based on a context model. The segmentation results by BHMT-3Sseg not only have more exact and more continuous edges, but also retain better region information. The experiments show that BHMT-3Sseg is efficient and effective for SAR image segmentation.

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HOU Biao, ZHAI Yan-Xia, JIAO Li-Cheng. Second Generation Bandelet-Domain Hidden Markov Tree-3S Model For SAR Image Segmentation[J]. Journal of Infrared and Millimeter Waves,2010,29(2):145~149

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  • Received:January 15,2009
  • Revised:September 14,2009
  • Adopted:March 25,2009
  • Online: April 07,2010
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