An adaptive image inpainting method based on the modified mumford-shah model and multiscale parameter estimation

Author:

Thanh D.N.H.1,Prasath V.B.S.2,Son N.V.3,Hieu L.M.4

Affiliation:

1. Department of Information Technology, Hue College of Industry, Hue 530000 VN

2. Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229 USA, Department of Biomedical Informatics, College of Medicine, University of Cincinnati, OH 45267 USA, Department of Electrical Engineering and Computer Science, University of Cincinnati, OH 45221 USA,

3. Department of Robotics and Production Adaptation, Tula State University, Tula 300012, Russia, Ballistic Research Laboratory, Military Weapon Institute, Hanoi 100000, Vietnam

4. Department of Economics, University of Economics, The University of Danang, Danang 550000, Vietnam

Abstract

Image inpainting is a process of filling missing and damaged parts of image. By using the Mumford-Shah image model, the image inpainting can be formulated as a constrained optimization problem. The Mumford-Shah model is a famous and effective model to solve the image inpainting problem. In this paper, we propose an adaptive image inpainting method based on multiscale parameter estimation for the modified Mumford-Shah model. In the experiments, we will handle the comparison with other similar inpainting methods to prove that the combination of classic model such the modified Mumford-Shah model and the multiscale parameter estimation is an effective method to solve the inpainting problem.

Publisher

Samara State National Research University

Subject

Electrical and Electronic Engineering,Computer Science Applications,Atomic and Molecular Physics, and Optics

Cited by 28 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3