Using Discrete Wavelet Transform and Wiener filter for Image De-nosing

Discrete Wavelet Transform

Authors

  • Mohammed M. Siddeq
  • Sadar Pirkhider Yaba

DOI:

https://doi.org/10.31185/jwsm.51

Keywords:

Discrete Wavelet Transform, Wiener filter, Estimates noise power

Abstract

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 nn , 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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Published

2022-10-03

Issue

Section

Articles

How to Cite

Siddeq, M. M., & Yaba, S. P. (2022). Using Discrete Wavelet Transform and Wiener filter for Image De-nosing: Discrete Wavelet Transform. Journal of Wasit for Science and Medicine, 2(2), 18-30. https://doi.org/10.31185/jwsm.51