General Regression Neural Network utilized for color transformation between images on RGB color space

The color transformation of images is utilized to enhance some potential features of a color image for wide applications in different fields. This paper presents a General regression analysis based algorithm for global color transformation between images. In this paper, General Regression Neural Network (GRNN) is respectively conducted on the R, G, and B planes of the target and source images to find the corresponding best fitting functions of each plane. The new values of each pixel of target image are then evaluated by using the best fitting functions. These new values are then combined into the result RGB color image. The experimental results show that the presented approach has two major advantages: (A) the proposed algorithm is manual free, simple, effective and accurate in transferring color between images without any change in the image details, (B) there are no restrictions in the image dynamic color ranges in the proposed algorithm.