Modeling colorization weight function based on natural color images
基于自然彩色图像的彩色化权值函数建模

Some existing function is assigned artificially as one of some kernel functions. It is hard to describe the affinity accurately between pixels in complicated texture area. Aiming at this problem, this paper employed a feature of natural color images in modeling weight function. It extrcted a local linear chrominance-luminance relation firstly from the distribution of pixels in RGB color space, and then served as prior assumption , generalized to the whole image with least square method, and finally provided a novel chrominance weight function model which could integrate luminance difference, space distance and luminance distribution of their neighborhoods into estimation of their chrominance affinity. Experiment results indicate that the weight function can benefit for better colorization, especially in complicated edges.