Interactive image matting for multiple layers

Image matting deals with finding the probability that each pixel in an image belongs to a user specified dasiaobjectpsila or to the remaining dasiabackgroundpsila. Most existing methods estimate the mattes for two groups only. Moreover, most of these methods estimate the mattes with a particular bias towards the object and hence the resulting mattes do not sum up to 1 across the different groups. In this work, we propose a general framework to estimate the alpha mattes for multiple image layers. The mattes are estimated as the solution to the Dirichlet problem on a combinatorial graph with boundary conditions. We consider the constrained optimization problem that enforces the alpha mattes to take values in [0; 1] and sum up to 1 at each pixel. We also analyze the properties of the solution obtained by relaxing either of the two constraints. Experiments demonstrate that our proposed method can be used to extract accurate mattes of multiple objects with little user interaction.