Sparse matrices in matlab: design and implementation
SIAM Journal on Matrix Analysis and Applications
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
ACM SIGGRAPH 2004 Papers
An Iterative Optimization Approach for Unified Image Segmentation and Matting
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
A Closed Form Solution to Natural Image Matting
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
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An image can be assumed to be a composite of the foreground and the background. The foreground and the background of each pixel are linearly combined in terms of this pixel's foreground opacity (called alpha). Image matting is the process of estimating the foreground, the background and the alpha for each pixel. In this paper, we transform the ill-posed image matting problem into two over-determined linear optimization problems by introducing two medium variables and imposing smoothness constraints. Closed form solutions can be obtained from the two problems. Extensive experimental results indicate that our algorithm can generate high-quality matting results.