Using Discrete Wavelet Transform and Wiener filter for Image De-nosing
Discrete Wavelet Transform
DOI:
https://doi.org/10.31185/jwsm.51Keywords:
Discrete Wavelet Transform, Wiener filter, Estimates noise powerAbstract
In this paper we proposed an algorithm for image de-nosing based on; the two level discrete wavelet transform (DWT), and Wiener filter, also this paper describe estimate noise power. At first The DWT transform noisy image into sub-bands, consist of lowfrequency
and high-frequencies, and then estimate noise power for each sub-band. The noise power is computed through two important computations; compute square of variance for each sub-band then compute the mean of the variance. After compute the variance apply the wiener filter on each sub-band by using local window nn , finally perform inverse DWT to obtain de-noised image. Our algorithm tested on the two color images and also compared with Normal Shrink filter and Wiener filter.
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Copyright (c) 2009 Mohammed M. Siddeq, Sadar Pirkhider Yaba

This work is licensed under a Creative Commons Attribution 4.0 International License.
