4.5 Article

Diffusion scheme using mean filter and wavelet coefficient magnitude for image denoising

Journal

Publisher

ELSEVIER GMBH, URBAN & FISCHER VERLAG
DOI: 10.1016/j.aeue.2016.04.012

Keywords

Image denoising; Mean filter; Local window

Funding

  1. National Natural Science Foundation of China [61401383, U1504603, 61572400]
  2. Qinglan Talent Program of Xianyang Normal University [XSYQL201503]
  3. Natural Science Foundation of Xianyang Normal University [14XSYK006]

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A novel wavelet-domain diffusion scheme is proposed for image denoising. In the proposed scheme, the shrinkage function plays an important role for denoising performance. By researching the signal information extraction feature map of locally adaptive linear minimum mean square-error estimation (LALMMSE) method, the proposed shrinkage function is produced. In the design of the function, local mean filter is used to effectively extract noise-free wavelet coefficient information while original noisy wavelet coefficient magnitude is used to offset the negative effect produced by information extraction. Tests show that the proposed new method is always on par with or better than the state-of-the-art image denoising techniques in the wavelet domain. Furthermore, the proposed method is also very efficient compared to other methods. (C) 2016 Elsevier GmbH. All rights reserved.

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