计算机工程与应用2026，Vol.62Issue(5)：293-301,9.DOI:10.3778/j.issn.1002-8331.2503-0304
动态图融合的图像和谐化方法
Image Harmonization Method for Dynamic Graph Fusion
摘要
Abstract
Image harmonization is a key task in computer vision,which aims to make the foreground compatible with the background of the composite image.To solve the problems of insufficient utilization of background information and destroyed visual coherence of the foreground region in existing local region matching-based harmonization methods,a dynamic graph fusion network(DGFNet)is proposed.In this network,the designed graph fusion module can adaptively construct the matching fusion relationship between the foreground and the background,and between the foreground and the fore-ground according to different input images.Among them,the background branch establishes a dynamic connection between the foreground and the highly similar background area through dynamic threshold screening,and thereby realizes fine-grained adjustment.The foreground self-fusion branch constructs a dynamic connection of foreground-related features to realize the internal matching fusion of the foreground and improve the local visual consistency of the image.In addition,the global perception decoder equipped with DGFNet uses the global background information to further globally calibrate the foreground.Experiments show that DGFNet reaches the state-of-the-art on both iHarmony4 and ccHarmony public datasets.关键词
图像和谐化/动态图/自适应匹配/全局感知Key words
image harmonization/dynamic graph/adaptive matching/global perception分类
信息技术与安全科学引用本文复制引用
程显贺,孟祥瑞,纪昂霄,张立华..动态图融合的图像和谐化方法[J].计算机工程与应用,2026,62(5):293-301,9.基金项目
国家重点研发计划项目(2021ZD0113501,2021ZD0113502) （2021ZD0113501,2021ZD0113502）
国家自然科学基金重大项目(82090052). （82090052）
