Grey-scale image colorization by local correlation based optimization algorithm

In this paper, we present a grey-scale image colorization technique by using local correlation based optimization algorithm. The core of our colorization method is to formalize the colorization 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 colorization a variety of grey-scale images. In our colorization 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 colorization 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 colorization methods. Additionally, by exploiting subsampling in YUV space, we accelerate the colorization process with nearly the same good results. Experiments show that better colorization results can be obtained faster with our method.