Fast natural image matting in perceptual color space

This paper proposes a fast natural image matting method in perceptual color space. Natural image matting is usually composed of three steps: region segmenting, color estimating and alpha estimating. Our matting approach uses a practical model to estimate the foreground and background color of a given pixel in unknown regions. It avoids complex computing and decreases computational cost significantly. A new alpha estimating method in perceptual color space is introduced to compute the alpha value correctly and effectively. We separate the chroma and intensity information of a color and emphasize the more significant one. Our method works well on different perceptual color spaces, extracts foreground objects much faster, and produces modestly better mattes than the Bayesian approach.