Abstract: Aming at the problems of lack of layering, blurring of details and poor visual effect in traditional emotion color transfer methods, a new transfer method is proposed by combining image decomposition and self-sparse fuzzy clustering. Firstly, in order to better maintain the details of the image, a cartoon texture decomposition based on low-rank texture prior is introduced to divide the source image into a smoothed map containing the main colors and a texture map with local information. Secondly, the self-sparse fuzzy clustering method is used to obtain the main representative colors and corresponding segmentation regions of the smooth map, enabling the result image to better retain the structure  of the source image.  Finally, an adaptive brightness correction anti-overflow strategy is designed, and based on this, a new emotional color transfer method is proposed to make the result image more consistent with human visual characteristics. Experimental results show that the proposed  method produces higher- quality transfer result images and performs better in both subjective and objective evaluations.

Key words: emotional color transfer, self-sparse fuzzy clustering, image decomposition, adaptive brightness correction, smoothing map