Multiscale Image Segmentation Using Wavelet-Domain Hidden Markov Models

被引:0
作者
Zhang, Jixiang [1 ]
Zhang, Xiangling [1 ]
机构
[1] Tianjin Univ Technol & Educ, Dept Elect Engn, Tianjin 300222, Peoples R China
来源
2008 4TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-31 | 2008年
关键词
hidden Markov tree model; image segmentation; texture; wavelet transform;
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
A new image segmentation algorithm based wavelet-domain, referred to as joint adaptive context and multiscale segmentation (JACMS) is developed. Towards achieving lower computational complexity, we propose a fast training algorithm, when applied to image segmentation, this technique provides a reliable initial segmentation. The contextual labeling tree which is used for the context-based Bayesian interscale fusion is studied. In order to achieve higher accuracies of both texture classification and boundary localization during the interscale fusion, we develop adaptive context structures which apply to homogeneous regions or/and texture boundaries, respectively. Experiments demonstrate that the proposed algorithms yield excellent segmentation results on both synthetic and real world data examples.
引用
收藏
页码:3180 / 3183
页数:4
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