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Adaptive Image Restoration via a Relaxed Regularization of Mean Curvature

Author

Listed:
  • Mingxi Ma
  • Jun Zhang
  • Chengzhi Deng
  • Zhaoyang Liu
  • Yuanyun Wang

Abstract

In this paper, a new relaxation model based on mean curvature for adaptive image restoration is proposed. To solve the problem efficiently, an alternating direction method of multipliers (ADMMs) is proposed. Furthermore, a rigorous convergence theory of the proposed algorithm is established. We also give the complexity analysis of our proposed method. Experimental results are provided to demonstrate the effectiveness and efficiency of the proposed method over a state-of-the-art method on synthetic and natural images.

Suggested Citation

  • Mingxi Ma & Jun Zhang & Chengzhi Deng & Zhaoyang Liu & Yuanyun Wang, 2020. "Adaptive Image Restoration via a Relaxed Regularization of Mean Curvature," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-11, December.
    • Handle: RePEc:hin:jnlmpe:3416907
    DOI: 10.1155/2020/3416907
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