关键词: 纹理聚类抠图, K近邻抠图, Laplacian矩阵, 闭形解

Abstract: To solve the problem that traditional matting methods do not perform well in highly textured regions, a Texture Clustering Matting (TCM) algorithm based on K-Nearest Neighbor (KNN) matting was proposed. First, the texture features were extracted. Second, a new feature space which contained color, position and texture information was constructed. Third, the matting Laplacian matrix was constructed by clustering neighbors in the new feature space. Last, the opacity was solved by using the closed-form solution. The experiments on benchmark datasets indicate that the overall ranking of the proposed method is significantly improved, which achieves relatively leading matting effect for highly textured image.

Key words: Texture Clustering Matting (TCM), K-Nearest Neighbor (KNN) matting, Laplacian matrix, closed-form solution