New image segmentation algorithm based on contextual information in wavelet domain

doi:10.3778/j.issn.1002-8331.2009.02.050

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (2): 173-175.DOI: 10.3778/j.issn.1002-8331.2009.02.050

• 图形、图像、模式识别 • Previous Articles Next Articles

New image segmentation algorithm based on contextual information in wavelet domain

LIU Guo-ying^1,2,WANG Lei-guang¹,MEI Tian-can³,SUN Tao³,QIN Qian-qing¹

1.State Key Laboratory of Information Engineering in Surveying，Mapping and Remote Sensing，Wuhan University，Wuhan 430079，China
2.Shool of Computer and Communication Engineering，Changsha University of Science & Technology，Changsha 410076，China
3.Shool of Electronic Information，Wuhan University，Wuhan 430079，China

Received:2008-07-01 Revised:2008-08-19 Online:2009-01-11 Published:2009-01-11
Contact: LIU Guo-ying

利用背景进行多尺度融合的多分辨率图像分割

刘国英^1,2,王雷光¹,梅天灿³,孙涛³,秦前清¹

1.武汉大学测绘遥感信息工程国家重点实验室，武汉 430079
2.长沙理工大学计算机与通信工程学院，长沙 410076
3.武汉大学电子信息学院，武汉 430079

通讯作者: 刘国英

Abstract

Abstract: In this paper，a new multiresolution segmentation algorithm—CLTVWseg，is presented based on contextual information in wavelet domain.In this method，a novel variable weighting parameter is employed to combine the feature random field and the label random field on each scale of wavelet decomposition.These two fields are successively in dominant role to obtain a more accurate segment result by the changing of the weighting parameter during the iterations on each scale.The interscale statistical dependencies between different scales of wavelet decomposition are included in the contextual information，and the segmentation at the finest resolution is used as the final result.Experiments have shown the high efficiency to obtain homogeneous regions and classification boundaries.

Key words: wavelet, Contextual Labeling Tree（CLT）, variable weighting parameter

摘要： 提出了一种基于背景的小波域多分辨率图像分割新方法—CLTVWseg。与常见的多分辨率分割方法不同，该方法采用背景信息来实现尺度间的交互；同时采用可变的权重参数连接小波分解的多尺度特征场和标记场。每一尺度上，通过权重参数的调整使得该尺度的特征场和标记场在分割过程中依次起主导作用，获得该尺度更为准确的分割结果。最细尺度上的分割结果作为该方法的分割结果。实验表明，该算法的分割结果，在保持边界的同时，区域一致性也比较好。

关键词: 小波, 背景标记树（CLT）, 可变权重

LIU Guo-ying^1,2,WANG Lei-guang¹,MEI Tian-can³,SUN Tao³,QIN Qian-qing¹. New image segmentation algorithm based on contextual information in wavelet domain[J]. Computer Engineering and Applications, 2009, 45(2): 173-175.

刘国英^1,2,王雷光¹,梅天灿³,孙涛³,秦前清¹. 利用背景进行多尺度融合的多分辨率图像分割[J]. 计算机工程与应用, 2009, 45(2): 173-175.

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New image segmentation algorithm based on contextual information in wavelet domain

利用背景进行多尺度融合的多分辨率图像分割

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