Image Segmentation Using Multiregion-Resolution MRF Model

被引:25
作者
Zheng, Chen [1 ]
Wang, Leiguang [2 ]
Chen, Rongyuan [3 ]
Chen, Xiaohui [4 ]
机构
[1] Henan Univ, Sch Math & Informat Sci, Kaifeng 475001, Peoples R China
[2] Southwest Forestry Univ, Sch Forestry, Kunming 650224, Peoples R China
[3] Hunan Univ Commerce, Management Engn Inst, Dept Informat, Changsha 410205, Hunan, Peoples R China
[4] Henan Univ, Kaifeng 475001, Peoples R China
基金
中国国家自然科学基金;
关键词
Image segmentation; Markov random field (MRF); multiresolution technique; region;
D O I
10.1109/LGRS.2012.2224842
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
The multiresolution technique is one of the most important techniques for image segmentation. Wavelet transformation is a pixel-based method and is widely used for multiresolution segmentation approaches, but it suffers the deficiency of modeling the macrotexture pattern of a given image. In order to overcome such a problem, this letter extends the multiresolution technique from the pixel level to the region level and proposes a new image segmentation model by incorporating the multiregion-resolution and the Markov random field model. Experiments are conducted using synthetic-aperture-radar data and remote sensing images, which demonstrates that our method can improve the segmentation accuracy compared with the multiresolution method based on the pixel level.
引用
收藏
页码:816 / 820
页数:5
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