Representative Color Transform for Image Enhancement

Hanul Kim, Su-Min Choi, Chang-Su Kim, Yeong Jun Koh; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 4459-4468


Recently, the encoder-decoder and intensity transformation approaches lead to impressive progress in image enhancement. However, the encoder-decoder often loses details in input images during down-sampling and up-sampling processes. Also, the intensity transformation has a limited capacity to cover color transformation between low-quality and high-quality images. In this paper, we propose a novel approach, called representative color transform (RCT), to tackle these issues in existing methods. RCT determines different representative colors specialized in input images and estimates transformed colors for the representative colors. It then determines enhanced colors using these transformed colors based on the similarity between input and representative colors. Extensive experiments demonstrate that the proposed algorithm outperforms recent state-of-the-art algorithms on various image enhancement problems.

Related Material

@InProceedings{Kim_2021_ICCV, author = {Kim, Hanul and Choi, Su-Min and Kim, Chang-Su and Koh, Yeong Jun}, title = {Representative Color Transform for Image Enhancement}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2021}, pages = {4459-4468} }