A Markov random field model-based approach to natural image matting

被引：4

作者：

Lin, Sheng-You ^{[1
]}

Shi, Jiao-Ying

机构：

[1] Zhejiang Inst Media & Commun, Dept Communicat Technol, Hangzhou 310018, Peoples R China

[2] Zhejiang Univ, State Key Lab CAD&CG, Hangzhou 310058, Peoples R China

来源：

JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY | 2007年 / 22卷 / 01期

关键词：

Markov random field; maximum a posteriori; blue screen matting; natural image matting; simulated annealing;

D O I：

10.1007/s11390-007-9022-x

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a Markov Random Field (MRF) model-based approach to natural image matting with complex scenes. After the trimap for matting is given manually, the unknown region is roughly segmented into several joint sub-regions. In each sub-region, we partition the colors of neighboring background or foreground pixels into several clusters in RGB color space and assign matting label to each unknown pixel. All the labels are modelled as an MRF and the matting problem is then formulated as a maximum a posteriori (MAP) estimation problem. Simulated annealing is used to find the optimal MAP estimation. The better results can be obtained under the same user-interactions when images are complex. Results of natural image matting experiments performed on complex images using this approach are shown and compared in this paper.

引用

页码：161 / 167

页数：7

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