Application of Wavelet and Wiener Filtering Algorithm in Image De-Noising - Open Access Library Journal

OALibJ > Vol.3 No.1, January 2016

Application of Wavelet and Wiener Filtering Algorithm in Image De-Noising ()

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DOI: 10.4236/oalib.1102319 2,168 Downloads 4,143 Views Citations

Author(s)

Yuanmei Wang, Tao Li

Affiliation(s)

School of Electronics and Information, Yangtze University, Jingzhou, China.

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.

KEYWORDS

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

Share and Cite:

Wang, Y. and Li, T. (2016) Application of Wavelet and Wiener Filtering Algorithm in Image De-Noising. Open Access Library Journal, 3, 1-7. doi: 10.4236/oalib.1102319.

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