测试科学与仪器2025，Vol.16Issue(3)：384-394,11.DOI:10.62756/jmsi.1674-8042.2025037
改进曲率Gabor变换和群稀疏表示的古壁画修复
Improved Gabor transform and group sparse representation for ancient mural inpainting
摘要
Abstract
Sparse representation has been highly successful in various tasks related to image processing and computer vision.For ancient mural image inpainting,traditional group sparse representation models usually lead to structure blur and line discontinuity due to the construction of similarity group solely based on the Euclidean distance and the randomness of dictionary initialization.To address the aforementioned issues,an improved curvature Gabor transform and group sparse representation(CGabor-GSR)model for ancient Dunhuang mural inpainting is proposed.To begin with,mutual information is introduced to weight the Euclidean distance,and then the weighted Euclidean distance acts as a new standard of similarity group.Subsequently,to mitigate the randomness of dictionary initialization,a curvature Gabor wavelet transform is proposed to extract the features and initialize the feature dictionary with dimension reduction based on principal component analysis(PCA).Ultimately,singular value decomposition(SVD)and split Bregman iteration(SBI)can be used to resolve the CGabor-GSR model to reconstruct the mural images.Experimental results on Dunhuang mural inpainting demonstrate tha the proposed CGabor-GSR achieves a better performance than compared algorithms in both objective and visual evaluation.关键词
数字图像处理/壁画修复/曲率Gabor小波变换/群稀疏表示/互信息Key words
digital image processing/mural inpainting/curvature Gabor wavelet transform/group sparse representation/mutual information引用本文复制引用
赵梦雪,陈永,陶美风..改进曲率Gabor变换和群稀疏表示的古壁画修复[J].测试科学与仪器,2025,16(3):384-394,11.基金项目
This work was supported by National Natural Science Foundation of China(No.61963023),Humanities and Social Sciences Youth Foundation of Ministry of Education(No.19YJC760012),and Lanzhou Jiaotong University Basic Top-Notch Personnel Project(No.2022JC36). （No.61963023）
