Edge detection in multispectral images
CVGIP: Graphical Models and Image Processing
SIGGRAPH '96 Proceedings of the 23rd 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
Image matting based on local color discrimination by SVM
Pattern Recognition Letters
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In image matting, several algorithms that produce high-quality results have recently been proposed; however, certain parameters have to be manually determined in order to obtain favorable results, which requires significant user effort. In this paper, we propose a method of automatically evaluating alpha mattes based on either of the two criteria: mutual information or correlation coefficient between the matte and the image gradient fields, and selecting optimal parameter values. This drastically reduces the user effort required for tuning parameters in image matting. The experimental results using several matting algorithms for various images show that the automatically selected alpha mattes are similar (or the same) to the manually selected optimal ones.