Abstract: Aiming at the problem that the structural information were easily lost in the process of decolorization, we proposed a decoloriz
ation algorithm based on structural information similarity. Firstly, the contrast image was constructed in RGB color space by using the average and standard deviation of pixels to keep the contrast and brightness information of the color image. Secondly, the similarity between each RGB channel image and contrast image was measured by structural similarity index. Finally, the structural similarity indices were taken as the weights in the global weighted mapping function to obtain the final grayscale image. This algorithm effectively solved the problem that the objective function needed to be solved in other typical decolorization algorithms, which resulted in the defects of high complexity and unnatural structural information. The experimental results on Cadik and CSDD database show that the proposed  algorithm is superior to some existing typical grayscale algorithms, which can effectively preserve the contrast and structural information of the original image and improve the computational efficiency. The visual perception is natural for the grayscale image, whose subjectivity and objective evaluation results are optimal.

Key words: decolorization, linear projection, structural information similarity, contrast, mapping function