Colorization of gray scale images in lαβ color space using mean and standard deviation

Abstract

Colorization of gray scale images is an appealing application of image processing. This work presents a technique of the gray image coloring. Here is introduced a general technique for “colorizing” grayscale images by transferring color between a source, color image and a destination or target, grayscale image. The approach presented here attempts to provide a method to help minimize the amount of human labor required for this task. Here we transfer the entire color “mood” of the source to the target image by matching luminance and texture information between the images. This work presents a technique of the gray image coloring, achieved using a very simple algorithm, and its core strategy is to choose a suitable color space and then to apply simple operations there. This work demonstrates that a color space with decorrelated axes is a useful tool for manipulating color images. Colorization of a gray scale image is achieved here by imposing mean and standard deviation onto the data points is a simple operation, which produces believable output images given suitable input images.