Grey-scale image colorization by local correlation based optimization algorithm

In this paper, we present a grey-scale image colonization technique by using local correlation based optimization algorithm. The core of our colonization method is to formalize the colonization problem as minimizing a quadratic cost function under some assumptions that are mainly based on the local image characters. It can be successfully applied in colonization a variety of grey-scale images. In our colonization method, users only need to freely scribble the desired color in the input grey-scale image, which is a great improvement upon the traditional manual colonization techniques. By introducing new local connectivity factor and distance factor, our approach can effectively alleviate the color diffuseness in different regions, which is one of main problem in previous colonization methods. Additionally, by exploiting subsampling in YUV space, we accelerate the colonization process with nearly the same good results. Experiments show that better colorization results can be obtained faster with our method.