二阶总广义变分图像修复模型及其算法

doi:10.3969/j.issn.1001-2400.2012.05.004

J4 ›› 2012, Vol. 39 ›› Issue (5): 18-23.doi: 10.3969/j.issn.1001-2400.2012.05.004

二阶总广义变分图像修复模型及其算法

许建楼^1,²;冯象初¹;郝岩^1,2

(1. 西安电子科技大学理学院，陕西西安 710071；
2. 河南科技大学数学与统计学院，河南洛阳 471003)

收稿日期:2011-12-29 出版日期:2012-10-20 发布日期:2012-12-13
通讯作者: 许建楼
作者简介:许建楼(1977-)，男，西安电子科技大学博士研究生，E-mail: xujianlou@126.com．
基金资助:
国家自然科学基金资助项目(60872138, 61105011, 11101292, 61271294)

Second order total generalized variational inpainting model and its algorithm

XU Jianlou^1,2;FENG Xiangchu¹;HAO Yan^1,2

(1. School of Science, Xidian Univ., Xi'an 710071， China;
2. School of Mathematics and Statistics, Henan Univ. of Science and Technology, Luoyang 471003， China)

Received:2011-12-29 Online:2012-10-20 Published:2012-12-13
Contact: XU Jianlou

摘要/Abstract

摘要：

为更好地修复图像，提出了一种新的图像修复模型．通过分析新模型的性质，给出了一种有效的原始对偶修复算法．实验结果表明，相比于总变分图像修复模型，新模型在修复结果上有更高的峰值信噪比和更好的视觉效果．

关键词: 图像修复, 总广义变分, 总变分, 原始对偶算法

Abstract:

In order to restore the damaged image better, this paper proposes a new second total generalized variation based image inpainting model. By analysing the properties of new model, an efficient primal-dual algorithm is introduced. Experimental results show that the new model is better than the total variation model in terms of both peak signal to noise ratio(PSNR) and visual effect.

Key words: image inpainting, total generalized variation, total variation, primal-dual algorithm

中图分类号:

TP391.41

许建楼;冯象初;郝岩. 二阶总广义变分图像修复模型及其算法[J]. J4, 2012, 39(5): 18-23.

XU Jianlou;FENG Xiangchu;HAO Yan. Second order total generalized variational inpainting model and its algorithm[J]. J4, 2012, 39(5): 18-23.

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二阶总广义变分图像修复模型及其算法

Second order total generalized variational inpainting model and its algorithm

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