Welcome To UTPedia

We would like to introduce you, the new knowledge repository product called UTPedia. The UTP Electronic and Digital Intellectual Asset. It stores digitized version of thesis, dissertation, final year project reports and past year examination questions.

Browse content of UTPedia using Year, Subject, Department and Author and Search for required document using Searching facilities included in UTPedia. UTPedia with full text are accessible for all registered users, whereas only the physical information and metadata can be retrieved by public users. UTPedia collaborating and connecting peoples with university’s intellectual works from anywhere.

Disclaimer - Universiti Teknologi PETRONAS shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.Best viewed using Mozilla Firefox 3 or IE 7 with resolution 1024 x 768.

SPECKLE NOISE REDUCTION USING MULTISCALE LMMSE (MLMMSE)-BASED FILTER

Zainal Abidin, Mohd Zulfadzlie (2013) SPECKLE NOISE REDUCTION USING MULTISCALE LMMSE (MLMMSE)-BASED FILTER. Universiti Teknologi Petronas. (Unpublished)

[img] PDF
Download (1650Kb)

Abstract

This report presents the project of studying the speckle noise reduction using Multiscale Least Minimum Mean Square Error (MLMMSE) filter. The MLMMSE filter is being compared in terms of feasibility, dependency and stability with the conventional image filter such as LEE 3X3, LEE 5X5, LEE 7X7 and Median filter. The estimation of the MLMMSE filter scheme for the image denoising is being proposed. Together with this project the wavelet selection to determine the best wavelet suit with MLMMSE filter is also being discussed. The principle of the speckle reduction is being used as the MLMMSE filtering are being perform with an undecimated domain wavelet. The image of the adaptive noise will be rescaling from the detail coefficient whereby the amplitude of the image signal will be divided with the variance ratio from the noisy image coefficient to the denoise image. This image is calculated analytically using the properties from the noisy image together with varying the variance and the selected optimal wavelet only. The original image is not resorting in order to obtain the result or to assessing the underlying backscattered signal. Experiment is carried out on normal image being test within two parameter that is Structural Similarity Index (SSIM) and Peak Signal Noise Ratio (PSNR) with varying the variance and the wavelet to identify the most suitable wavelet to run with MLMMSE filter for ultrasound images. The equivalent number of looks (ENL) is analysed in the last part of the experiment to demonstrate visual image quality is achieved for excellency in terms of the dependency of the images itself and also to avoid the typical of impairments of the images which normally created from the critically subsampled in the wavelet-based image denoising.

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Digital Electronics - Design
Subject: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Engineering > Electrical and Electronic
Depositing User: Users 2053 not found.
Date Deposited: 23 Oct 2013 08:53
Last Modified: 25 Jan 2017 09:38
URI: http://utpedia.utp.edu.my/id/eprint/9491

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...