测试科学与仪器2025，Vol.16Issue(2)：195-204,10.DOI:10.62756/jmsi.1674-8042.2025019
结构与纹理混合增强的生成对抗壁画修复算法
Generative adversarial mural inpainting algorithm based on structural and texture hybrid enhancement
摘要
Abstract
For the existing deep learning image restoration methods,the joint guidance of structure and texture information is not considered,which leads to structural disorder and texture blur in the restoration results.A generative adversarial mural inpainting algorithm based on structural and texture hybrid enhancement was proposed.Firstly,the structure guidance branch composed of dynamic convolution cascade was constructed to improve the expression ability of structure features,and the structure information was used to guide the encoder coding to enhance the edge contour information of the coding feature map.Then,the multi-granularity feature extraction module was designed to obtain the texture features of texture guided branches,and the multi-scale texture information was used to guide the decoder to reconstruct and repair,so as to improve the texture consistency of murals.Finally,skip connection was used to promote the feature sharing of structure and texture features,and the spectral-normalized PatchGAN discriminator was used to complete the mural restoration.The digital restoration experiment results of real Dunhuang murals showed that the proposed method was better than the comparison algorithms in both subjective and objective evaluation,and the restoration results were clearer and more natural.关键词
图像处理/壁画修复/结构与纹理增强/动态卷积/多粒度特征提取Key words
image processing/mural inpainting/structural and texture enhancement/dynamic convolution/multi-granularity feature extraction引用本文复制引用
陶美风,陈永,赵梦雪,张娇娇..结构与纹理混合增强的生成对抗壁画修复算法[J].测试科学与仪器,2025,16(2):195-204,10.基金项目
This work was supported by Ministry of Education in China Project of Humanities and Social Sciences(No.19YJC760012) （No.19YJC760012）
Star of Innovation Project for Outstanding Graduate Students in Gansu Province(No.2022CXZX-546) （No.2022CXZX-546）
