江苏大学学报（自然科学版）2026，Vol.47Issue(3)：316-322,7.DOI:10.3969/j.issn.1671-7775.2026.03.009
弱光环境下基于图像增强的视觉惯性定位方法
Visual-inertial localization method based on image enhancement under low-light environments
摘要
Abstract
To solve the problems of pose drift and localization failures by traditional visual-inertial methods in mobile systems of intelligent vehicles and robots under low-light conditions,the novel visual-inertial localization method was developed by incorporating image enhancement techniques into the VINS-Mono framework.In the front end of VINS-Mono algorithm,the input image stream was processed with multi-scale Retinex enhancement.The contrast-limited adaptive histogram equalization and the photometric correction module featuring with adaptive correction factor were applied.The weighted fusion strategy based on the average grayscale value and entropy of the processed images was employed to integrate the results.Using wheeled robot for data collection,the trajectory accuracy comparison experiment was conducted.The results show that compared to the scheme without image enhancement and the scheme with baseline enhancement,the proposed method reduces the root mean square error of trajectory tracking by the average of 22.74％and 8.57％,respectively.The proposed approach significantly improves the localization accuracy of visual-inertial navigation systems under low-light environments.关键词
弱光环境/视觉惯性定位/特征提取/图像增强/VINS-Mono/自适应矫正/多尺度高斯函数Key words
low-light environment/visual-inertial localization/feature extraction/image enhancement/VINS-Mono/adaptive correction/multi-scale Gaussian function分类
信息技术与安全科学引用本文复制引用
江浩斌,傅世友,李傲雪,任俊豪,刘光耀..弱光环境下基于图像增强的视觉惯性定位方法[J].江苏大学学报（自然科学版）,2026,47(3):316-322,7.基金项目
江苏省产业前瞻与共性关键技术竞争项目(BE2017129) （BE2017129）
