关键词: 优化式着色, K最邻近结点算法（KNN）, 二次着色, 图层信息

Abstract: It is possible to recolorize images by applying existing scribble based colorization algorithms for grayscale images, which omitting colors in original images. This paper proposes an optimized method to improve the existing image recolorization technologies. In comparison with the optimization-based colorization, the proposed method features in: （i） using K Nearest Neighbors（KNN） to preprocess images into stratified layers and learn from their content to produce a new simulated weight function; （ii） colorizing images in terms of the optimized layer-based weights and hence producing optimized colorizations. Extensive experimental results show that the proposed algorithm can solve the problem of color leakage at the boundary of the object, and obtain accurate color images. Compared with previous methods, the proposed algorithm is more robust to color blending in the input data.

Key words: optimization-based colorization, K Nearest Neighbors（KNN）, recolorization, layers information