Ms. Lu Li Profile

Lu Li

at Beijing Institute of Technology

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Proceedings Article | 4 January 2023 Presentation + Paper

Self-supervised learning exposure correction via histogram equalization prior

Lu Li, Daoyu Li, Shuai Wang, Qiang Jiao, Liheng Bian

Proceedings Volume 12317, 1231707 (2023) https://doi.org/10.1117/12.2643015

KEYWORDS: Histograms, Image processing, Image enhancement

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Poor lighting conditions in the real world may lead to ill-exposure in captured images which suffer from compromised aesthetic quality and information loss for post-processing. Recent exposure correction works address this problem by learning the mapping from images of multiple exposure intensities to well-exposed images. However, it requires a large number of paired training data, which is hard to implement for certain data-inaccessible scenarios. This paper presents a highly robust exposure correction method based on self-supervised learning. Specifically, two sub-networks are designed to deal with under- and over-exposed regions in ill-exposed images respectively. This hybrid architecture enables adaptive ill-exposure correction. Then, a fusion module is employed to fuse the under-exposure corrected image and the over-exposure corrected image to obtain a well-exposed image with vivid color and clear textures. Notably, the training process is guided by histogram-equalized images with the application of histogram equalization prior (HEP), which means that the presented method only requires ill-exposed images as training data. Extensive experiments on real-world image datasets validate the robustness and superiority of this technique.

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