Image Matting Based on Weighted Color and Texture Sample Selection

Color sampling based matting methods find the best known samples for foreground and background colors of unknown pixels. Such methods do not perform well if there is an overlap in the color distribution of foreground and background regions. Furthermore, current sampling based matting methods choose samples that are located around the boundaries of foreground and background regions. The contribution of texture and color is automatically estimated by analyzing the content of the image. The method uses texture to complement color in extracting accurate mattes in images when foreground and background colors overlap. This is handled by designing an objective function that uses weighted contribution of color and texture information to select the best (F,B) pair for unknown samples. The final matte is further refined using conventional Laplacian method. The image quality enhancement parameters applied to matting image to produce high visual quality output.