Performance and quality assurance of medical image using hybrid thresholding wavelet transform with Wiener filter. Issue 3 (3rd July 2022)

• Record Type: Journal Article
• Authors: Naimi, Hilal
• Is Part Of: Australian journal of electrical & electronics engineering. Volume 19:Issue 3(2022)
• Page Start: 294
• Page End: 299
• Publication Date: 2022-07-03
• Subjects: Denoising -- discrete wavelet transform -- stationary wavelet transform -- bayesShrink -- Wiener filter; Electrical engineering -- Periodicals; Electronics -- Periodicals; Periodicals; 621.305
• DOI: 10.1080/1448837X.2022.2034350
• Languages: English
• ISSNs: 1448-837X

Abstract

ABSTRACT: Medical images like X-ray, computed tomography, ultrasound, and magnetic resonance imaging (MRI) are produced using different techniques; during this process, noise is added that decreases the image quality and image analysis. Image denoising is an important task in image processing; use of wavelet transform improves the quality of an image and reduces noise level. We propose in this research, a denoising approach basing on discrete wavelet transform (DWT) using Hybrid Thresholding (bayesShrink) with Wiener filter technique for enhancing the quality image. This technique improved a better balance between smoothness and accuracy than the traditional wavelet DWT and are less redundant than stationary wavelet transform (SWT). In addition, the Structural Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR) were used to analyse the denoised images quality.