Abstract
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.
Original language | English |
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Title of host publication | Proceedings - 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 4439-4448 |
Number of pages | 10 |
ISBN (Electronic) | 9781665428125 |
DOIs | |
Publication status | Published - 2021 |
Event | 18th IEEE/CVF International Conference on Computer Vision, ICCV 2021 - Virtual, Online, Canada Duration: 2021 Oct 11 → 2021 Oct 17 |
Publication series
Name | Proceedings of the IEEE International Conference on Computer Vision |
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ISSN (Print) | 1550-5499 |
Conference
Conference | 18th IEEE/CVF International Conference on Computer Vision, ICCV 2021 |
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Country/Territory | Canada |
City | Virtual, Online |
Period | 21/10/11 → 21/10/17 |
Bibliographical note
Funding Information:This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Korea government (MSIT) (No.NRF-2018R1A2B3003896, No. NRF-2019R1F1A1062907, and No. NRF-2021R1A4A1031864)
Publisher Copyright:
© 2021 IEEE
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition