计算机应用研究2024，Vol.41Issue(1)：314-320,7.DOI:10.19734/j.issn.1001-3695.2023.06.0285
噪声指导下过滤光照风格实现低光照场景的语义分割
Filtering illumination style under guidance of noise to achieve semantic segmentation of low-light scenes
摘要
Abstract
Low-light image segmentation is always the difficulty of image segmentation.The low contrast and high fuzziness caused by low light make this kind of image segmentation much more difficult than general image segmentation.In order to im-prove the accuracy of semantic segmentation in low light environment,this paper proposed a semantic segmentation model of low light scene with filtering light style under noise guidance(SFIS)according to the characteristics of low-light image.The model comprehensively used signal-to-noise ratio as prior knowledge,and adopted different distance interaction for different noise regions in the image by guiding the self-attention operation in the long distance branch and the feature fusion of long/short distance branches.This paper also further designed an illumination filter,which was a module that further extracted the il-lumination style information from the overall style of the image.By alternately training the illumination filter and the semantic segmentation model,the lighting style gap between different lighting conditions was gradually reduced,so that the segmentation network could learn illumination invariant features.The proposed model outperforms the previous work on the dataset LLRGBD and achieves the best results.The mIoU on the real dataset LLRGBD-real reaches 66.8％,it shows that the proposed long and short distance branch module and the illumination filter module can effectively improve the semantic segmentation ability of the model in low light environment.关键词
语义分割/低光照/注意力机制/域自适应Key words
semantic segmentation/low light/attention mechanism/domain adaptation分类
信息技术与安全科学引用本文复制引用
罗俊,宣士斌,刘家林..噪声指导下过滤光照风格实现低光照场景的语义分割[J].计算机应用研究,2024,41(1):314-320,7.基金项目
国家自然科学基金资助项目(61866003) （61866003）
广西民族大学研究生教育创新计划资助项目(gxun-chxs2021063) （gxun-chxs2021063）
