基于DR-IFMM的岩画图像修复方法研究
作者:
作者单位:

1.桂林理工大学南宁分校计算机应用学院 南宁 532100;2.山东建筑大学信息与电气工程学院 济南 250101

中图分类号:

TP391.4;TN919.8

基金项目:

广西哲学社会科学研究课题(23BMZ003)项目资助


Inpainting method for rock art images based on DR-IFMM
Author:
Affiliation:

1.College of Computer Application, Guilin University of Technology at Nanning,Nanning 532100, China;2.School of Information and Electrical Engineering, Shandong Jianzhu University,Jinan 250101, China

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    摘要:

    为复原受损的岩画图像,本文提出一种基于DR-IFMM的图像修复方法。该方法通过图像损伤区域的像素密度确定两个最佳修复半径,并分别应用于IFMM算法生成修复图像,IFMM算法在FMM算法基础上改进权重计算规则。随后将两幅图像重组为最优修复图像。实验结果表明,DR-IFMM方法对不同损伤的岩画图像修复效果优于MSMM、IK-means、COTR、STDecomposition、SFIIM、AutoFill以及ICriminisi方法,有效解决岩画图像中出现的颜色缺失、纹理混乱等问题。与LaMa方法相比,本文方法的优势在于无需模型训练以及性能强大的计算机配置,也能够取得较好的修复效果。修复的岩画图像可用于数字化文化遗产的保护,有助于岩画的传承与发扬,同时为文物研究人员提供一部完整的刻在石壁上的中国“史书”。

    Abstract:

    A method based on the DR-IFMM is proposed for inpainting damaged rock art images. This method determines two optimal repair radii based on the pixel density of the damaged region, and is applied to the IFMM algorithm to generate the repaired image respectively. The IFMM algorithm improves the weight calculation rules based on the FMM algorithm, and then fuses and restructures the two images into the optimal repaired image. The experimental results show that the DR-IFMM method outperforms the MSMM, IK-means, COTR, STDecomposition, SFIIM, AutoFill and ICriminisi methods in inpainting rock art images with various types of damages, and effectively addresses the issues such as color loss and texture clutter. Compared with the LaMa method, the advantage of the proposed approach is that it still can achieve better inpainting results without model training and high-performance computer. Inpainting damaged rock art images can inherit and develop the rock art through the form of digital. and provide cultural relic researchers with a complete record of China′s ′history′ etched on stone walls.

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李树威,刘国政,房淑宇,刘晓彤,吕金阳.基于DR-IFMM的岩画图像修复方法研究[J].电子测量技术,2025,48(7):16-27

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  • 在线发布日期: 2025-05-12
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