Adaptive highlight removal through generative adversarial networks and color adjustment

Shengrui Jiang; Li Cheng; Haiwen Yuan; Xuan Li

doi:10.1117/12.3033742

13 June 2024 Adaptive highlight removal through generative adversarial networks and color adjustment

Shengrui Jiang, Li Cheng, Haiwen Yuan, Xuan Li

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 131806S (2024) https://doi.org/10.1117/12.3033742
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

The detection and removal of highlights are fundamental issues in computer vision and image processing. However, existing methods for highlight removal have certain drawbacks. For example, many existing methods are not suitable for repairing large highlight areas, and the applicability of current methods is relatively limited, requiring re-adjustment of parameters in different usage scenarios. Therefore, this paper proposes an effective deep learning model that can address highlight issues in a wide range of scenarios, specifically designed for removing highlights in individual images. The proposed approach is to first detect the positions of highlights and generate a highlight mask. The training process consists of two main parts. Initially, the highlight removal network is trained. This network, based on a generative adversarial network, generates information about the portions of the image affected by highlights. However, there may still be color deviations in the original highlight positions after generation. To address this, the desthighlighted image and the highlight mask are fed into a color adjustment network for secondary training. This corrects the colors in the repaired area, ultimately producing the final image after highlight removal.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shengrui Jiang, Li Cheng, Haiwen Yuan, and Xuan Li "Adaptive highlight removal through generative adversarial networks and color adjustment", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 131806S (13 June 2024); https://doi.org/10.1117/12.3033742

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KEYWORDS

Image processing

Image restoration

Education and training

Image enhancement

Image fusion

Light sources and illumination

Reflection

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