Applications and Analyses on Post Processing in Image Matting

Image matting is a process which separates the foreground object from the background scene, and the key of matting is to compute the alpha matte. The existing sampling based matting methods are always in a discretized strategy, which could results in a great deal of discontinuities and noises in final alpha mattes. Post processing is thus introduced to enhance the smoothness and to further increase the accuracy of the final matte. However, the corresponding review articles are still lacking in the field of international research of post-processing in image matting. Moreover, the quantitative evaluation of alpha mattes still remains unsolved. This paper firstly classifies the post-processing step into two basic categories: affinity-combined and self-smoothing. Next, the advantages and disadvantages are both summarized and analyzed. Finally, the alpha mattes after post-processing are evaluated in quantitative manner comprehensively, which improves the problem of pure visual evaluation in traditional methods.