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Speckle Noise Reduction in Ultrasound Images by Wavelet Thresholding based on Subband Mean Difference

Md. Motiur Rahman, Muhammad Azim, Mina, Md. Shorif Uddin


In image processing, image is corrupted by different type of noises. But generally ultrasound image is corrupted by speckle noise. Speckle noise is multiplicative noise so it’s difficult to remove the multiplicative noise as compared to additive noise. The traditional techniques are not very good for especially speckle noise reduction. In this paper, we present a wavelet based thresholding scheme for noise reduction in ultrasound images based on sub band mean differences. To find threshold value we compute the arithmetic mean of general decomposed subband and then perform single level farther decomposed of that general subband to compute the arithmetic mean of its diagonal subband. Quantitative and qualitative comparisons with existing speckle noise reduction methods demonstrate its higher performance in terms of the Peak Signal to Noise Ratio (PSNR).


Ultrasound image, Speckle noise, Wavelet transform, Subband Mean Difference, Thresholding.

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