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Priori Knowledge Makes Low-Light Image Enhancement More Reasonable.

Zefei Chen1, Yongjie Lin1, Jianmin Xu1

  • 1School of Civil Engineering & Transportation, South China University of Technology, Guangzhou 510641, China.

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|September 13, 2025
PubMed
Summary

This study introduces Priori Deep Curve Estimation (Priori DCE), a novel framework for low-light image enhancement. Priori DCE utilizes prior knowledge to guide brightness and adaptively adjust pixel enhancement, significantly improving image quality metrics.

Keywords:
GA Blockpriori channelspriori enhancement/suppression probabilitypriori knowledge

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Area of Science:

  • Computer Vision
  • Image Processing
  • Artificial Intelligence

Background:

  • Low-light image enhancement is challenging due to inherent uncertainties in brightness mapping.
  • Existing methods struggle with adaptive pixel brightness adjustments and global visual balance.

Purpose of the Study:

  • To develop a priori knowledge-based framework for robust low-light image enhancement.
  • To address the ill-posed nature of low-light image enhancement by guiding brightness.
  • To improve visual balance and detail preservation in enhanced images.

Main Methods:

  • Incorporation of priori channels to guide the brightness of enhanced images.
  • Development of an enhancement function that adaptively adjusts priori enhancement probability based on pixel brightness.
  • Introduction of the Global-Attention Block (GA Block) for inter-pixel computation and visual balance.

Main Results:

  • Priori DCE demonstrates significant advantages over state-of-the-art methods on the LOLv2-Synthetic dataset.
  • Achieved improvements in PSNR (25.67 to 29.49) and SSIM (92.82 to 93.6) compared to Retinexformer.
  • Reduced the NIQE index from 3.94 to 3.91, indicating enhanced perceptual quality.

Conclusions:

  • Priori DCE effectively enhances low-light images by leveraging prior knowledge and adaptive strategies.
  • The proposed framework offers superior performance in terms of quantitative metrics and perceptual quality.
  • The Global-Attention Block is crucial for achieving visual balance in low-light image enhancement.