Gray image colorization in YCbCr color space

Abstract

Gray Scale image colorization is an appealing area in the world of image processing. This work presents a simple process for colorizing gray image, using a colored image which is similar to this gray scale image but not the colorized version of the gray image. Here we convert both these images to a decorrelated color space YCbCr and then divide these images into small windows of equal size, then we calculate mean and standard deviation for data points based on luminance values in each of these windows to compute a luminance measure and we also extract texture features like energy, entropy, contrast, correlation and homogeneity based on correlation matrix for each of these windows. We apply proper weights to these texture features to calculate a texture similarity measure & then calculate a similarity measure based on the texture similarity measure and luminance measure for each of these windows in both the images. Then we compare each window in gray scale image with every other window in colored image using this similarity measure and find the best matching window. Then the chromatic properties of this colored window are transferred to the gray window pixel by pixel and colorization of gray scale image is achieved, which produces believable results.