Natural Image Matting Based on Weak Assumptions and Regularization Strategy

The Bayesian matting method has two drawbacks in function modeling and solving method. First, we design a computation measure to correct the fixed variance and propose a Gaussian model with adaptive variance to reflect the complex distribution of nature images texture. Second, we proposed a solving method based on the regularization strategy, which adds data constrain term and penalty term into the original method through the Augmented Lagrangian Multiplier. Finally, the experimental results show that our method outperforms other methods in complex texture areas.