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Ju, S.G., He, K. and Zhou, J.L. (2010) Image with Gauss Noise De-Noising Based on Neighborhood Characteristics. Journal of Sichuan University, 42, 139-144.

has been cited by the following article:

• TITLE: Application of Wavelet and Wiener Filtering Algorithm in Image De-Noising

  AUTHORS: Yuanmei Wang, Tao Li

  KEYWORDS: Image De-Noising, Threshold Function, Wavelet Soft Threshold, Wiener Filtering

  JOURNAL NAME: Open Access Library Journal, Vol.3 No.1, January 26, 2016

  ABSTRACT: Image is often easily polluted by noise in the process of image processing, so image de-noising is an important step in the field of image processing. Based on the wavelet threshold de-noising algorithm, an improved image de-noising algorithm based on wavelet and Wiener filter is proposed in this paper, which can effectively reduce the Gaussian white noise. Firstly we use wavelet soft threshold to reduce noise, then use Wiener filter to process the image and get the valuation of the image. Experimental results show that the proposed algorithm on image de-noising not only can effectively suppress Gaussian white noise, but also can well retain the details of image edges.