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

  • Siddeq M
  • Yaba S
N/ACitations
Citations of this article
7Readers
Mendeley users who have this article in their library.

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 lowfrequencyand 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.

Cite

CITATION STYLE

APA

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

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free