Color Decoupling for Multi-Illumination Color Constancy
Current multi-illumination color constancy methods typically estimate illumination for each pixel directly. However, according to the multi-illumination imaging equation, the color of each pixel is determined by various components, including the innate color of the scene content, the colors of multiple illuminations, and the weightings of these illuminations. Failing to distinguish between these components results in color coupling. On the one hand, there is color coupling between illumination and scene content, where estimations are easily misled by the colors of the content, and the distribution of the estimated illuminations is relatively scattered. On the other hand, there is color coupling between illuminations, where estimations are susceptible to interference from high-frequency and heterogeneous illumination colors, and the local contrast is low. To address color coupling, we propose a Color Decoupling Network (CDNet) that includes a Content Color Awareness Module (CCAM) and a Contrast HArmonization Module (CHAM). CCAM learns scene content color priors, decoupling the colors of content and illuminations by providing the model with the color features of the content, thereby reducing out-of-gamut estimations and enhancing consistency. CHAM constrains feature representation, decoupling illuminants by mutual calibration between adjacent features. CHAM utilizes spatial correlation to make the model more sensitive to the relationships between neighboring features and utilizes illumination disparity degree to guide feature classification. By enhancing the uniqueness of homogeneous illumination features and the distinctiveness of heterogeneous illumination features, CHAM improves local edge contrast. Additionally, by allocating fine-grained margin coefficients to emphasize the soft distinctiveness of similar illumination features, further enhancing local contrast. Extensive experiments on single- and multi-illumination benchmark datasets demonstrate that the proposed method achieves superior performance.
Authors
- Zhijiang Li (ORCID: https://orcid.org/0000-0002-8440-4672)
- Zhenshan Tan (ORCID: https://orcid.org/0000-0003-3466-5417)
- L. Zhang (ORCID: https://orcid.org/0009-0003-1535-4987)
- Wen Zhang (ORCID: https://orcid.org/0009-0008-1519-4692)
Institutions
- Nanjing University of Information Science and Technology (CN)
- Wuhan University (CN)
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN)
Publication Details
- Journal
- IEEE Transactions on Circuits and Systems for Video Technology
- Published
- 2024-12-26
- DOI
- https://doi.org/10.1109/tcsvt.2024.3523019
- Citations
- 2
- Primary Topic
- Color Science and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.68