Cost Filtered Matting with Radom Texture Features

Chen Qiu-feng; Shen Qun-tai; Liu Peng-fei

doi:10.11999/JEIT150143

Volume 37 Issue 11

Nov. 2015

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(11): 2578-2586

Chen Qiu-feng, Shen Qun-tai, Liu Peng-fei. Cost Filtered Matting with Radom Texture Features[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2578-2586. doi: 10.11999/JEIT150143

Citation:

Chen Qiu-feng, Shen Qun-tai, Liu Peng-fei. Cost Filtered Matting with Radom Texture Features[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2578-2586. doi: 10.11999/JEIT150143

Chen Qiu-feng, Shen Qun-tai, Liu Peng-fei. Cost Filtered Matting with Radom Texture Features[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2578-2586. doi: 10.11999/JEIT150143

Citation:

Chen Qiu-feng, Shen Qun-tai, Liu Peng-fei. Cost Filtered Matting with Radom Texture Features[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2578-2586. doi: 10.11999/JEIT150143

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Cost Filtered Matting with Radom Texture Features

doi: 10.11999/JEIT150143

1.
(School of Information Science and Engineering, Central South University, Changsha 410083, China)
2.

Funds:

The National Natural Science Foundation of China (61473318, 60974048)

Received Date: 2015-01-27
Rev Recd Date: 2015-06-29
Publish Date: 2015-11-19

Abstract

Abstract

In order to deal with the color overlap problem in matting, a fast random projection method is proposed to complement the color information. First, the raw texture matrix is obtained through dense abstraction from color image. The random projection is performed and the best three texture channels are chosen by the foreground and background overlap factors. Combining the texture image, the new cost function takes into account texture, color, and spatial information. Second, the filtering process is carried out to the sample selection cost, including the effect of the local and nonlocal neighbors. Finally, the relationship between iterative filter and global energy smooth is proven, and the post filter formula is obtained. Experiments show that the cost filtered matting with random texture features produces both visually and quantitatively better results when the color distributions of the foreground and background are similar.
- Image processing,
- Texture matting,
- Random projection,
- Cost filtering,
- Iterative smooth

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References(16)

References

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