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
收藏
页码：251 / 257
页数：7
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