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ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

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TOWARDS A WAVELET BASED MEDICAL IMAGE ENHANCEMENT<br />

PROCEDURE<br />

1. ABSTRACT<br />

M. Pinheiro 1 , F. Martins 2 and J.L. Alves 3<br />

In this work we present a comparative study between three of the most relevant<br />

Wavelet-based image enhancement algorithms in the literature and apply them in the<br />

denoising of phantom head Modified Shepp-Logan medical images. The results obtained<br />

corroborate the conclusions drawn in [12], however is does not seem to be the best<br />

approach for Wavelet-based image denoising.<br />

2.INTRODUCTION<br />

Wavelet analysis provides a time or space-scale representation of signals that has found<br />

in the last few decades a wide range of applications in areas such as physics, signal and<br />

image processing, applied mathematics, among others. The basic idea of the Wavelet<br />

Transform is to locally decompose the signal in contributions belonging to different<br />

scales [1]. This representation unfolds the time-space and frequency and enables the<br />

spatial localization of relevant short lasting signal events. In order to accomplish that,<br />

two parameters are needed, one to handle the frequency or scale a and other to<br />

manipulate the time or space b. Given the values of parameters a and b there can be<br />

defined a set of analysing wavelets by applying a series of dilations and translations to a<br />

single base wavelet (or mother wavelet

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