J4 ›› 2014, Vol. 41 ›› Issue (5): 141-147.doi: 10.3969/j.issn.1001-2400.2014.05.024

• 研究论文 • 上一篇    下一篇



  1. (1. 西安电子科技大学 数学与统计学院,陕西 西安  710071;
    2. 西安医学院 公共课部,陕西 西安  710021)
  • 收稿日期:2013-05-16 出版日期:2014-10-20 发布日期:2014-11-27
  • 通讯作者: 吴玉莲
  • 作者简介:吴玉莲(1978-),女,西安电子科技大学博士研究生,E-mail:wyl_wp711@163.com.
  • 基金资助:


Nonconvex image inpainting via balanced regularization approach

WU Yulian1,2;FENG Xiangchu1   

  1. (1. School of Mathematics and Statistics, Xidian Univ., Xi'an  710071, China;
    2. Common Course Department, Xi'an Medical College, Xi'an  710021, China)
  • Received:2013-05-16 Online:2014-10-20 Published:2014-11-27
  • Contact: WU Yulian



关键词: 图像修复, 卡通纹理, 非凸, 紧框架


Real images usually have two layers, namely, cartoons and textures, both of these layers have sparse approximations under some tight frame systems such as curvelet, local DCTs, and B-spline wavelet. In this paper, we solve the image inpainting problem by using two separate tight frame systems which can sparsely represent the two parts of the image. Different from existing schemes in the literature which are either analysis-based or synthesis-based sparsity priors, our minimization formulation applies the nonconvex sparsity prior via the balanced approach. We also derive iterative algorithms for finding their solutions. Numerical simulation examples are given to demonstrate that our proposed nonconvex method achieves significant improvements over the classical l1 sparse method and the variation TV method in image inpainting.

Key words: image inpainting, cartoons and textures, nonconvex, tight frame systems