SPECKLE NOISE REDUCTION USING ADAPTIVE MULTISCALE PRODUCTS THRESHOLDING

Bukhari, Nur Arash (2014) SPECKLE NOISE REDUCTION USING ADAPTIVE MULTISCALE PRODUCTS THRESHOLDING. [Final Year Project] (Unpublished)

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Abstract

Image denoising is an essential preprocessing technique in image acquisition systems. For instance, in ultrasound (US) images, suppression of speckle noise while preserving the edges is highly preferred. Thus, in this paper denoising the speckle noise by using wavelet-based multiscale product thresholding approach is presented. The underlying principle of this technique is to apply dyadic wavelet transform and performs the multiscale products of the wavelet transform. Then, an adaptive threshold is calculated and applied to the multiscale products instead of applying it on wavelet coefficient. Thereafter, the performance of the proposed technique is compared with other denoising techniques such as Lee filter, boxcar filter, linear minimum mean square error (LMMSE) filter and median filter. The result shows that the proposed technique gives a better performance in terms of PNSR and ENL value by an average gain of 1.22 and 1.8 times the noisy on, respectively and can better preserved image details

Item Type: Final Year Project
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments / MOR / COE: Engineering > Electrical and Electronic
Depositing User: Users 2053 not found.
Date Deposited: 20 Feb 2014 11:35
Last Modified: 25 Jan 2017 09:37
URI: http://utpedia.utp.edu.my/id/eprint/13463

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