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November 20, 2025Applied SciencesOpen Access

A Novel Low-Illumination Image Enhancement Method Based on Convolutional Neural Network with Retinex Theory

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Authors

HMHaixia MaoWPWei PengYTYan Tian

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Overview

Novel technique improves image clarity and reduces halo phenomena in low-light conditions using convolutional neural networks and image fusion.

Key Points

  • Retinex-CNN enhances images with improved clarity and brightness, reducing halo phenomena with notable effectiveness.
  • Key metrics included PSNR and SSIM improvements across datasets, demonstrating superior performance in low-illumination conditions.
  • Assessment involving both synthetic and real image datasets ensured comprehensive evaluation of the enhancement process.
  • This novel image processing approach may enable advanced applications in computer vision, improving robustness in challenging lighting conditions.

Cite This Study

Mao et al. (2025) studied this question.

synapsesocial.com/papers/6924f07ac0ce034ddc34ff2fhttps://doi.org/10.3390/app152212324
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Also Consider

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  1. 1A Retinex-based network for image enhancement in low-light environments2024 · 9 citations
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  4. 4An Improved Retinex-Based Approach Based on Attention Mechanisms for Low-Light Image Enhancement2024 · 6 citations
  5. 5Retinex-based low-light image enhancement with multi-channel feature optimization2026