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 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.
CITATION STYLE
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
Mendeley helps you to discover research relevant for your work.