developed a color space, called lab, which minimizes correlation between chan-nels for many natural scenes., This space is based on data-driven human perception research that assumes the human visual system is ideally suited for processing natural scenes. What we want is an orthogonal color space without correlations between the axes. This complicates any color modification process. This implies that if we want to change the appearance of a pixel's color in a coherent way, we must modify all color channels in tandem. For example, in RGB space, most pixels will have large values for the red and green channel if the blue channel is large. When a typical three channel image is represented in any of the most well-known color spaces, there will be correlations between the different channels'val-ues. Our goal is to do so with a simple algorithm, and our core strategy is to choose a suitable color space and then to apply simple oper-ations there. We can imagine many methods for applying the colors of one image to another. Figure 1 shows an example of this process, where we applied the colors of a sunset photograph to a daytime computer graphics rendering. This article describes a method for a more general form of color correction that borrows one image's color characteristics from anoth-er. Often this means removing a dominant and undesirable color cast, such as the yellow in photos taken under incandescent illumination. This method proved its success in coloring images compared to the traditional method adoption of fixed weights for coloring images because it relies on fixed weights for converting all grayscale images. Skewness, Mean and Standard deviation moments have been extracted from the features of grayscale images and its adoption the determine weights of the RGB color system. The basic idea in this paper is to employ the mathematics equations which extracted from grayscale image in conversion operation, this paper presents the method of coloring the grayscale image by using the weights derived from the characteristics of the grayscale image. The method of converting color images from the RGB color system to grayscale images is a simple operation by using the fixed weights method of conversion, but using the same weights to restore the color of the same images is not an effective operation of all types of images because the grayscale image contains little information and it isn't worthy of conversion operation.
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