Localized Image Matte Evaluation by Gradient Correlation

In natural image matting, various kinds of algorithms have been recently proposed. Moreover, alpha matting results have also been generated for comparison and composition into new backgrounds. However, all these methods have to make an alpha matte comparison to the ground truth so that one can get the final pixel-wised evaluation of these results. Nevertheless, while the input datasets are just used for test and there are no ground truth mattes, it is not possible to perform comparisons and to generate the quantitative comparison results. In this paper we combine the two ideas above and propose a new pixel-wise alpha mattes evaluation method. This approach is based on using local windows to measure gradient correlation between image and the matte. An optimal image channel minimizing the image variance is also selected at each window in order to perform the correlation more correctly. Experimental result shows that, our system can generate precise evaluation result for each pixel of each matte without ground truth.