内蒙古民族大学学报（自然科学版）2026，Vol.41Issue(4)：52-58,7.DOI:10.14045/j.cnki.15-1220.2026.04.007
应对低光度下的变电站开关柜指示灯图像增强网络
An Image Enhancement Network for Indicator Lights of Substation Switchgear under Low Light Conditions
摘要
Abstract
In response to the problem in substation robot inspections where low light conditions lead to poor qual-ity capture of switch gear indicator light images,uneven illumination,and severe noise interference,affecting subsequent state detection,this paper propose a low-light indicator image enhancement network tailored for this scenario.The model connects multiple structures composed of an improved frequency-domain self-attention mechanism and a feature refinement feed-forward network to achieve precise extraction of global and local features.Combined with a brightness adjustment module,it progressively optimizes the illumination distribution and reduces feature loss through multiple re-sidual connections.Experiments show that the model performs excellently on a self-built substation indicator light data-set.Compared with advanced algorithms such as Uformer and EnlightenGAN,it achieves a PSNR of 23.89,an increase of 1.10 over the optimal comparative model LLFormer;a SSIM of 0.864,an increase of 0.061;and a LPIPS of 0.103,a decrease of 0.024.It can effectively improve the brightness of low-light images,suppress noise,and enhance illumina-tion uniformity,providing high-quality image support for inspection robots to accurately recognize indicator light states.关键词
变电站指示灯/图像增强/低光度图片/特征提取Key words
substation indicator lights/image enhancement/low-light images/feature extraction分类
信息技术与安全科学引用本文复制引用
吴晓强,边慧龙,邬开俊,辛子昊..应对低光度下的变电站开关柜指示灯图像增强网络[J].内蒙古民族大学学报（自然科学版）,2026,41(4):52-58,7.基金项目
内蒙古自治区重点研发与成果转化计划项目(2023YFDZ0043) （2023YFDZ0043）
