光学精密工程2025，Vol.33Issue(7)：1114-1129,16.DOI:10.37188/OPE.20253307.1114
LightDiffu-DCE:基于光照强度扩散的低光照图像增强
LightDiffu DCE:low light image enhancement based on light intensity diffusion
摘要
Abstract
A Light Diffusion-based Zero-Reference Deep Curve Estimation algorithm(LightDiffu-DCE)is proposed to address the uneven distribution of light intensity from multiple sources in low-light images,which often results in the loss of image contour features and unnatural enhancement effects.To improve the model's generalization capability,a diffusion model grounded in light intensity modeling of light sourc-es is employed to generate training datasets with varied illumination levels.Subsequently,a depth profile estimation network incorporating edge feature fusion is designed to extract richer multi-scale contour and detail features,thereby enhancing the accuracy of light intensity estimation.Furthermore,atmospheric light estimation is integrated to calculate the illumination of different image regions,enabling dynamic fine-tuning of enhancement curves and coefficients for more natural lighting recovery.Experimental evaluations on the challenging ExDark(non-contrast)and LOL(contrast)datasets,utilizing six rigorous metrics,demonstrate the superiority of LightDiffu-DCE.Specifically,on the ExDark dataset,improvements of ap-proximately 8.35%,6.20%,and 21.83%are achieved in the no-reference metrics NIQE,PIQE,and RISQ,respectively;on the LOL dataset,gains of approximately 12.12%,4.76%,and 49.89%are ob-served in the reference-based metrics PSNR,SSIM,and RMSE.These results substantiate that LightDif-fu-DCE effectively enhances low-light images,restoring clarity,vividness,and naturalness.关键词
计算机视觉/扩散模型/低光照增强/边缘特征/深度曲线估计网络Key words
computer vision/diffusion model/low light intensity enhancement/edge features/depth curve estimation network分类
计算机与自动化引用本文复制引用
闫光辉,吴佰靖,马龙..LightDiffu-DCE:基于光照强度扩散的低光照图像增强[J].光学精密工程,2025,33(7):1114-1129,16.基金项目
国家自然科学基金资助项目(No.62062049,No.62366028) （No.62062049,No.62366028）
中央引导地方科技发展资金资助项目(No.22ZY1QA005) （No.22ZY1QA005）
兰州交通大学重点研发项目(No.ZDYF2304) （No.ZDYF2304）
