A Review of Image Denoising Using Fuzzy and Wiener Filters in the Wavelet Domain

Geetika Agotra; Prof. Manish Kumar Singhal

doi:10.32628/IJSRST2411430

Authors

Geetika Agotra M.Tech Scholar, Department of Information Technology (IT), NRI Institution of Information Science & Technology (NIIST)-BHOPAL, Madhya Pradesh, India Author
Prof. Manish Kumar Singhal Associate Professor & H.O.D, 2Associate Professor & H.O.D, NRI Institution of Information Science & Technology (NIIST)-BHOPAL, Madhya Pradesh, India Author

DOI:

https://doi.org/10.32628/IJSRST2411430

Keywords:

ATMED, ATMEV, RMSE, PSNR, Wavelet Transform

Abstract

This paper focuses on image denoising using fuzzy wavelet domain transforms, reviewing recent advancements in this area. Wavelet transforms have become a powerful tool in image denoising, with one of the most widely used techniques involving thresholding wavelet coefficients. The paper proposes a hybrid denoising method that combines the wavelet transform, median filtering, and nonlinear diffusion. Additionally, a novel fuzzy filter is introduced to reduce additive noise in digital color images. Two distinct image denoising techniques are discussed: the first employs an Asymmetrical Triangular Moving Average Filter (TMAV) with a HAAR wavelet transform, while the second utilizes an Asymmetrical Triangular Median Filter (TMED) with the HAAR wavelet transform.

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