Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Regularization Parameter Selection for Total Variation Model Based on Local Spectral Response

  • Zheng, Yuhui (Jiangsu Engineering Centre of Network Monitoring, College of Computer and Software, Nanjing University of Information Science and Technology) ;
  • Ma, Kai (Jiangsu Engineering Centre of Network Monitoring, College of Computer and Software, Nanjing University of Information Science and Technology) ;
  • Yu, Qiqiong (College of Math and Statistics, Nanjing University of Information Science and Technology) ;
  • Zhang, Jianwei (College of Math and Statistics, Nanjing University of Information Science and Technology) ;
  • Wang, Jin (College of Information Engineering, Yangzhou University)
  • Received : 2017.08.04
  • Accepted : 2017.09.26
  • Published : 2017.10.31
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Abstract

In the past decades, various image regularization methods have been introduced. Among them, total variation model has drawn much attention for the reason of its low computational complexity and well-understood mathematical behavior. However, regularization parameter estimation of total variation model is still an open problem. To deal with this problem, a novel adaptive regularization parameter selection scheme is proposed in this paper, by means of using the local spectral response, which has the capability of locally selecting the regularization parameters in a content-aware way and therefore adaptively adjusting the weights between the two terms of the total variation model. Experiment results on simulated and real noisy image show the good performance of our proposed method, in visual improvement and peak signal to noise ratio value.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China

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