Improved global-sampling matting using sequential pair-selection strategy

This paper addresses the problem of natural image matting in which the goal is to softly-segment a foreground from a background. Given an input image and some known foreground (FG) and background (BG) pixels, an alpha value indicating a partial foreground coverage is calculated for every other pixel in the image. The proposed algorithm is affiliated to the sampling-based matting techniques where the alpha of every unknown pixel is calculated using some FG / BG pairs that are sampled according to certain criteria. Current sampling based matting techniques suffer from critical disadvantages, leaving the problem open for further development. By adopting a novel FG / BG pair-selection strategy, we propose a technique that overcomes critical pitfalls in the state-of-the-art methods with a performance that is comparable (and superior in certain cases) to them. Our results were evaluated according to the matting online benchmark.