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    • Low-light image enhancement with diagonal frequency feature refinement and truncated sampling in conditional diffusion models

    • The research progress in the field of low light image enhancement was introduced, and relevant experts proposed a conditional diffusion model low light image enhancement method based on frequency domain feature optimization and truncated sampling. This provides a new solution to solve the problems of high computational cost, high-frequency feature distortion, and color shift in existing methods.
    • Pages: 1-15(2026)   

      Received:19 July 2025

      Revised:2026-01-30

      Accepted:10 February 2026

      Online First:11 February 2026

    • DOI: 10.11834/jig.250342     

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  • Li Wengai, Gui Ke, Xiao Zhaolin, Jin Haiyan, Su Haonan. Low-light image enhancement with diagonal frequency feature refinement and truncated sampling in conditional diffusion models[J/OL]. Journal of Image and Graphics,2026,1-15. DOI: 10.11834/jig.250342 DOI:
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Li Yan 武汉大学计算机学院;武汉大学国家网络安全学院
Huang Ji 中国科学技术大学计算机学院
Zou Qin 武汉大学计算机学院;人工智能与数字经济广东省实验室
Li Qingquan 人工智能与数字经济广东省实验室
Li Wenqi 复旦大学计算机科学技术学院
Zhou Keyang 复旦大学计算机科学技术学院
Hu Xiaoxiao 复旦大学计算机科学技术学院
Zhang Xinpeng 复旦大学计算机科学技术学院

相关机构

Laboratory of Artificial Intelligence and Digital Economy
School of Computer Science and Technology, University of Science and Technology of China
School of Cyber Science and Engineering, Wuhan University
School of Computer Science, Wuhan University
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