A local color transfer method based on optimal transmission

Xianshen Zhu; Enliang Hu

doi:10.1117/12.3009533

16 October 2023 A local color transfer method based on optimal transmission

Xianshen Zhu, Enliang Hu

Proceedings Volume 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023); 128031S (2023) https://doi.org/10.1117/12.3009533
Event: 2023 5th International Conference on Artificial Intelligence and Computer Science (AICS 2023), 2023, Wuhan, China

Abstract

How to transmit better the color distribution of one image to another image is an interesting problem in computer image generation, and the optimal transmission mathematical theory has been applied to the research field of this type of problem. In response to the common problems of color distribution differences or lack of hierarchy between the transmitted result image and the reference image in existing methods, this paper proposes a new color transfer method: first, we segment the foreground and background regions of the reference image and the specify image; Then we use the optimal transmission theory to transfer the colors of the foreground and background regions separately; Finally, we merge and enhance the transmitted regions to obtain the resulting image. The experimental results show that compared to the two image color transfer methods in the literature, the method proposed in this paper can better transfer the color distribution of reference images to specify image, preserve the hierarchical sense of the original specify image, and achieve better visual effects.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xianshen Zhu and Enliang Hu "A local color transfer method based on optimal transmission", Proc. SPIE 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023), 128031S (16 October 2023); https://doi.org/10.1117/12.3009533

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