Global Optimization of Deviation Rectification for Image Matting

A global algorithm of optimization of deviation rectification for image matting is presented,which treats the process of image matting as that of graph partition after carefully comparing image segmentation with image matting.While minimizing the cost of soft segmentation between foreground object and background,the approach can maximize the degree of association among the foreground objects.Both theoretical analysis and experimental process are studied to demonstrate that the proposed method can be more efficient to extract global optimal matte compared with other function expressions of matting optimization.This research will have a contribution to the implementation of automatic or semi-automatic matting.