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Image Denoising via Asymptotic Nonlocal Filtering

Author

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  • Xiaoyan Liu
  • Xiangchu Feng
  • Xuande Zhang
  • Xiaoping Li
  • Liang Luo

Abstract

The nonlocal means algorithm is widely used in image denoising, but this algorithm does not work well for high-intensity noise. To overcome this shortcoming, we establish a coupled iterative nonlocal means model in this paper. Considering the computation complexity of the new model, we realize it by using multiscale wavelet transform and propose an asymptotic nonlocal filtering algorithm which can reduce the influence of noise on similarity estimation and computation complexity. Moreover, we build a new nonlocal weight function based on the structure similarity index. Simulation results indicate that the proposed approach cannot only remove the noise but also preserve the structure of image and has good visual effects, especially for highly degenerated images.

Suggested Citation

  • Xiaoyan Liu & Xiangchu Feng & Xuande Zhang & Xiaoping Li & Liang Luo, 2015. "Image Denoising via Asymptotic Nonlocal Filtering," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-9, February.
    • Handle: RePEc:hin:jnlmpe:340182
    DOI: 10.1155/2015/340182
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