BL_Wiener Denoising Method for Removal of Speckle Noise in Ultrasound Image

Authors

  • Suhaila Sari Universiti Tun Hussein Onn Malaysia
  • Zuliana Azreen Zulkifeli Universiti Tun Hussein Onn Malaysia
  • Hazli Roslan universiti tun hussein onn malaysia
  • Nabilah Ibrahim universiti tun hussein onn malaysia

Keywords:

Ultrasound imaging, denosing technique, speckle noise, Bilateral Filter, Adaptive Wiener Filter, BL_Wiener

Abstract

Medical imaging techniques are extremely important tools in medical diagnosis. One of these important imaging techniques is ultrasound imaging. However, during ultrasound image acquisition process, the quality of image can be degraded due to corruption by speckle noise. The enhancement of ultrasound images quality from the 2D ultrasound imaging machines is expected to provide medical practitioners more reliable medical images in their patients’ diagnosis. However, developing a denoising technique which could remove noise effectively without eliminating the image’s edges and details is still an ongoing issue. The objective of this paper is to develop a new method that is capable to remove speckle noise from the ultrasound image effectively. Therefore, in this paper we proposed the utilization of Bilateral Filter and Adaptive Wiener Filter (BL_Wiener denoising method) for images corrupted by speckle noise. Bilateral Filter is a non-linear filter effective in removing noise, while Adaptive Wiener Filter balances the tradeoff between inverse filtering and noise smoothing by removing additive noise while inverting blurring. From our simulation results, it is found that the BL_Wiener method has improved between 0.89 [dB] to 3.35 [dB] in terms of PSNR for test images in different noise levels in comparison to conventional methods.

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Author Biographies

  • Suhaila Sari, Universiti Tun Hussein Onn Malaysia
    1. Faculty of Electrical and Electronic Engineering,Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.
    2. Biomedical Engineering Modelling and Simulation Research Group (BioMems), Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.
    3. Artifical Intelligence and Computing Vision Research Group (AICoV), Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.
  • Zuliana Azreen Zulkifeli, Universiti Tun Hussein Onn Malaysia
    1. Faculty of Electrical and Electronic Engineering,Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.
  • Hazli Roslan, universiti tun hussein onn malaysia
    1. Faculty of Engineering Technology, Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.
  • Nabilah Ibrahim, universiti tun hussein onn malaysia
    1. Faculty of Electrical and Electronic Engineering,Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.
    2. Biomedical Engineering Modelling and Simulation Research Group (BioMems), Universiti Tun Hussein Onn Malaysia, 86400 Johor, MALAYSIA.

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Issue

Section

Issue on Electrical and Electronic Engineering

How to Cite

Sari, S., Zulkifeli, Z. A., Roslan, H., & Ibrahim, N. (2015). BL_Wiener Denoising Method for Removal of Speckle Noise in Ultrasound Image. International Journal of Integrated Engineering, 6(3). https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/1041