A comprehensive study on digital image matting
Natural image matting refers to the problem of extracting the region of interest such as foreground object from an image based on user inputs like scribbles or trimap. Matting is an ill-posed problem inherently since we need to output three images out of only one input image. After a comprehensive survey and analysis of the existing matting literature, we observe that there are three key components in better estimating the alpha values, that is, the design of matting laplacian matrix, the definition of neighborhood and the choices of feature space. Based on this observation, we introduce a unified framework for digital image matting, which provides the possibility of obtaining a better understanding and direction of further improvement for image matting problem. The experimental results tested on different matting algorithms further prove the feasibility of our proposed framework.