Wiener filter and wavelet transform of noisy image analysis based on MATLAB
- 1 School of Electronic Information, School of Northwestern Polytechnical University, Xi 'an, Shaanxi Province, 710100, China.
* Author to whom correspondence should be addressed.
Abstract
In recent years, how to filter noise more effectively has been a topic of great interest, and improvements have been made based on various filtering algorithms in the hope of obtaining the most optimal filtering effect with the least amount of computation. However, there is a considerable research gap in how to achieve this goal. This article is based on this research. The motif of this study paper is the analysis of images containing Gaussian noise based on Wiener filter and wavelet transform, and an attempt to improve the filtering algorithm. The SNR and PSNR obtained by applying Wiener filtering analysis are 46.7864 and 76.0247, respectively, and the SNR and PSNR results of wavelet transform are 14.0851 and 49.7426. this article implements Wiener filtering based on Wiener method, and the results are almost consistent with the function of invoked system. It is found that the Wiener filter is more suitable for handling processing Gaussian noise. The SNR and PSNR values of both sets of experimental Wiener filter are larger than those of wavelet transform, then it indicates that Wiener filter is more beneficial to suppress Gaussian noise under the same condition.
Keywords
Wiener filter, wavelet transform
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Cite this article
Liu,Z. (2023). Wiener filter and wavelet transform of noisy image analysis based on MATLAB. Applied and Computational Engineering,5,786-792.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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