An adaptive image inpainting method based on the modified Mumford-Shah model and multiscale parameter estimation

被引：26

作者：

Thanh, D. N. H. ^{[1
]}

Prasath, V. B. S. ^{[2
,3
,4
]}

Son, N. V. ^{[5
,6
]}

Hieu, L. M. ^{[7
]}

机构：

[1] Hue Coll Ind, Dept Informat Technol, Hue 530000, Vietnam

[2] Cincinnati Childrens Hosp Med Ctr, Div Biomed Informat, Cincinnati, OH 45229 USA

[3] Univ Cincinnati, Coll Med, Dept Biomed Informat, Cincinnati, OH 45267 USA

[4] Univ Cincinnati, Dept Elect Engn & Comp Sci, Cincinnati, OH 45221 USA

[5] Tula State Univ, Dept Robot & Prod Adaptat, Tula 300012, Russia

[6] Mil Weapon Inst, Ballist Res Lab, Hanoi 100000, Vietnam

[7] Univ Danang, Univ Econ, Dept Econ, Danang 550000, Vietnam

来源：

COMPUTER OPTICS | 2019年 / 43卷 / 02期

关键词：

image inpainting; Mumford-Shah model; modified Mumford-Shah model; regularization; Euler-Lagrange equation; inverse gradient; multiscale; NOISE REMOVAL;

D O I：

10.18287/2412-6179-2019-43-2-251-257

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

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.

引用

页码：251 / 257

页数：7

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