STUDY OF WAVELET BASED SPECKLE REDUCTION METHODS FOR ULTRASOUND IMAGES

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BOORBOOR HOSSEIN BEYGI F.; ABOU ALHASANI MOHAMMAD JAVAD; AHMADIANI A.

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Paper Information

Journal: IRANIAN JOURNAL OF MEDICAL PHYSICS Year:2005 | Volume:2 | Issue:6 Page(s): 33-44

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Title

STUDY OF WAVELET BASED SPECKLE REDUCTION METHODS FOR ULTRASOUND IMAGES

Author(s)

BOORBOOR HOSSEIN BEYGI F. | ABOU ALHASANI MOHAMMAD JAVAD | AHMADIANI A. | Issue Writer Certificate

Keywords

SONOGRAPHYQ4

SPECKLE NOISEQ4

FILTERINGQ3

WAVELET TRANSFORMQ4

THRESHOLDINGQ4

BAYESIANQ4

PDFQ4

Abstract

Introduction: Although Ultrasound imaging has many advantages such as being; noninvasive, nonionizing, less expense, real-time, portable, it has some disadvantages making the quality of its image poor. The most important artifact in an ultrasound image is SPECKLE NOISE, thus many researches and approaches such as various kinds of FILTERING (mean, median, wiener) and other wavelet based methods have been developed for reducing such noise. In this work, we have studied and compared the result of implemention of these methods.Materials and Methods: In order to compare various methods for SPECKLE NOISE reduction, some parameters such as MSE (Mean Square Error), S/MSE (Signal to Mean Square Error) and beta factor are defined. Using MATLAB Package, these methods are implemented some kidney ultrasound images with added artificial SPECKLE NOISE.Results: According to our results it is found that ordinary and adaptive FILTERING methods not only can not reduce SPECKLE NOISE adequately, but also they blured images. Therefore, they aren't good choice for SPECKLE NOISE reduction. Among other methods which are able to reduce speckle using WAVELET TRANSFORM, it seems that universal THRESHOLDING method make image blured. In spite of the fact that BAYESIAN method could preserve details of image and reduce SPECKLE NOISE adequately, due to its complex algorithm, large computation of the parameters of the PDF's (alpha, gamma, sigma) does not make it appropriate candidate. However bayes and normal THRESHOLDING approaches, due to their beta parameter close to one, and better SNR than universal THRESHOLDING, and the fact that they have less computation in compare with BAYESIAN approach, are the most appropriate methods for reducing SPECKLE NOISE for SONOGRAPHY images.Conclusion: in order to our achievement it can be deduced that bayes and normal threresholding methods are the most efficient and useful methods.

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