Image Denoising Using Multiwavelet Transform with Different Filters and Rules

Dublin Core

Title

Image Denoising Using Multiwavelet Transform with Different Filters and Rules

Subject

Denoising
Multiwavelet
Thresholding
Soft Thresholding

Description

Image denoising is a technique for removing unwanted signals called the noise, which coupling with the original signal when transmitting them; to remove the noise from the original signal, many denoising methods are used. In this paper, the Multiwavelet Transform (MWT) is used to denoise the corrupted image by Choosing the HH coefficient for processing based on two different filters Tri-State Median filter and Switching Median filter. With each filter, various rules are used, such as Normal Shrink, Sure Shrink, Visu Shrink, and Bivariate Shrink. The proposed algorithm is applied Salt& pepper noise with different levels for grayscale test images. The quality of the denoised image is evaluated by using Peak Signal to Noise Ratio (PSNR). Depend on the value of PSNR that explained in the result section; we conclude that the (Tri-State Median filter) is better than (Switching Median filter) in denoising image quality, according to the results of applying rules the result of the Shrinking rule for each filter shows that the best result using first the Bivariate Shrink.

Creator

Majeed Laftah, Muna

Source

International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 15 (2021); pp. 140-151
1865-7923

Publisher

International Association of Online Engineering (IAOE), Vienna, Austria

Date

2021-08-11

Rights

Copyright (c) 2021 Muna Majeed Laftah

Relation

Format

application/pdf

Language

eng

Type

info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article

Identifier

Citation

Majeed Laftah, Muna, Image Denoising Using Multiwavelet Transform with Different Filters and Rules, International Association of Online Engineering (IAOE), Vienna, Austria, 2021, accessed November 5, 2024, https://igi.indrastra.com/items/show/2074

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