Abstract: Speckle noise in ultrasound (US) medical images is the prime factor that undermines its full utilization. This noise is added by the constructive / destructive interference of sound waves travelling through hard- and soft-tissues of a patient. It is therefore generally accepted that the noise is unavoidable. As an alternate researchers have proposed several algorithms to somewhat undermine the effect of speckle noise. The discrete wavelet transform (DWT) has been used by several researchers. However, the performance of only a few transforms has been demonstrated. This paper provides a comparison of several DWT. The algorithm comprises of a pre-processing stage using Wiener filter, and a post-processing stage using Median filter. The processed image is compared with the original image on four metrics: two are based on full-reference (FR) image quality assessment (IQA), and the remaining two are based on no-reference (NR) IQA metrics. The FR-IQA are peak signal-to-noise ratio (PSNR) and mean structurally similarity index measure (MSSIM). The two NR-IQA techniques are blind pseudo-reference image (BPRI), and blind multiple pseudo-reference images (BMPRI). It has been demonstrated that some of these wavelet transforms outperform others by a significant margin.

Asim ur Rehman Khan, Farrokh Janabi-Sharifi, Mohammad Ghahramani and Muhammad Ahsan Rehman Khan, “Comparison of Reducing the Speckle Noise in Ultrasound Medical Images using Discrete Wavelet Transform” International Journal of Advanced Computer Science and Applications(IJACSA), 10(5), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100542

@article{Khan2019,
title = {Comparison of Reducing the Speckle Noise in Ultrasound Medical Images using Discrete Wavelet Transform},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100542},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100542},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {5},
author = {Asim ur Rehman Khan and Farrokh Janabi-Sharifi and Mohammad Ghahramani and Muhammad Ahsan Rehman Khan}
}