南京信息工程大学学报2025，Vol.17Issue(1)：22-30,9.DOI:10.13878/j.cnki.jnuist.20240705002
基于中高位视频监控的图像及视频质量增强算法
Image and video quality enhancement based on medium and high-altitude video surveillance
摘要
Abstract
To address the issues inherent in existing image and video restoration and enhancement techniques,this paper proposes a neural network model approach rooted in semantic feature extraction.Firstly,an image restoration and enhancement framework centered on semantic feature is introduced,followed by the joint optimization of degra-dation and reconstruction models.The proposed model is validated on a publicly accessible dataset and compared with existing algorithms.The results indicate that the proposed approach achieves a 50%improvement in RankIQA(Rank Image Quality Assessment)scores compared to the state-of-the-art super-resolution algorithm PULSE(Photo Upsampling via Latent Space Exploration).Furthermore,the quality scores of the enhanced images and videos are comparable to those of the original HD ones.In terms of user evaluation,81%of the reconstructed results are consid-ered to be superior to those produced by the comparison algorithms,demonstrating that the proposed approach offers higher quality in reconstructed images and videos.关键词
视频增强/图像重建/感知质量/语义特征/语义理解Key words
video enhancement/image reconstruction/perceptual quality/semantic feature/semantic understanding分类
信息技术与安全科学引用本文复制引用
向涛,葛宁,宋奇蔚..基于中高位视频监控的图像及视频质量增强算法[J].南京信息工程大学学报,2025,17(1):22-30,9.基金项目
国家重点研发计划"变革性技术关键科学问题"重点专项(2018YFA0701601) （2018YFA0701601）
