Improving Sampling Criterion for Alpha Matting
Jun Sheng Cheng, Zhenjiang Miao · 2013
Natural image matting is a useful and challenging task when processing image or editing video. It aims at solving the problem of accurately extracting the foreground object of arbitrary shape from an image by use of user-provided extra information, such as trimap. In this paper, we present a new sampling criterion based on random search for image matting. This improved random search algorithm can effectively avoid leaving good samples out and can also deal well with the relation between nearby samples and distant samples. In addition, an effective cost function is adopted to evaluate the candidate samples. The experimental results show that our method can produce high-quality mattes.