基于Contourlet域HMT和D-S证据融合的SAR图像分割

针对Contourlet的多尺度、局部化、方向性和各向异性等优点,结合隐马尔科夫树(hidden Markov tree,HMT)模型和D-S(Dempster-Shafer)证据理论,提出一种新的SAR图像分割算法.该算法首先将隐马尔科夫树模型推广到Contourlet域,在多尺度HMT上采用D-S证据融合理论有效地...

Fusion Segmentation Algorithm for SAR images based on HMT in Contourlet Domain and D-S theory of evidence

Abstract: Utilizing the contourlet’s advantages of multiscale ,localization, directionality and anisotropy, a new SAR image segmentation algorithm based on hidden markov tree (HMT) in contourlet domain and dempster-shafer theory of evidence is proposed in this paper. The algorithm extends the hidden markov tree framework to contourlet domain and fuses the clustering and persistence of contourlet transform using HMT model and D-S theory, and then, we deduce the maximum a posterior (MAP) segmentation equation for the new fusion model. The algorithm is used to segment the real SAR images. Experimental results and analysis show that the proposed algorithm effectively reduces the influence of multiplicative, improves the segmentation accuracy and provides a better visual quality for SAR images over the algorithms based on HMT-MRF in the wavelet domain, HMT and MRF in the Contourlet domain, respectively.