Despeckling Algorithm for Removing Speckle Noise from Ultrasound Images

Ultrasound (US) imaging can examine human bodies of various ages; however, in the process of obtaining a US image, speckle noise is generated. The speckle noise inhibits physicians from accurately examining lesions; thus, a speckle noise removal method is essential technology. To enhance speckle noi...

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Main Authors: Hyunho Choi, Jechang Jeong
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Symmetry
Subjects:
Online Access:https://www.mdpi.com/2073-8994/12/6/938
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spelling doaj-cebd01ce2b4746c2811327743d9662c72020-11-25T02:39:16ZengMDPI AGSymmetry2073-89942020-06-011293893810.3390/sym12060938Despeckling Algorithm for Removing Speckle Noise from Ultrasound ImagesHyunho Choi0Jechang Jeong1Department of Electronics and Computer Engineering, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul 04763, KoreaDepartment of Electronics and Computer Engineering, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul 04763, KoreaUltrasound (US) imaging can examine human bodies of various ages; however, in the process of obtaining a US image, speckle noise is generated. The speckle noise inhibits physicians from accurately examining lesions; thus, a speckle noise removal method is essential technology. To enhance speckle noise elimination, we propose a novel algorithm using the characteristics of speckle noise and filtering methods based on speckle reducing anisotropic diffusion (SRAD) filtering, discrete wavelet transform (DWT) using symmetry characteristics, weighted guided image filtering (WGIF), and gradient domain guided image filtering (GDGIF). The SRAD filter is exploited as a preprocessing filter because it can be directly applied to a medical US image containing speckle noise without a log-compression. The wavelet domain has the advantage of suppressing the additive noise. Therefore, a homomorphic transformation is utilized to convert the multiplicative noise into additive noise. After two-level DWT decomposition is applied, to suppress the residual noise of an SRAD filtered image, GDGIF and WGIF are exploited to reduce noise from seven high-frequency sub-band images and one low-frequency sub-band image, respectively. Finally, a noise-free image is attained through inverse DWT and an exponential transform. The proposed algorithm exhibits excellent speckle noise elimination and edge conservation as compared with conventional denoising methods.https://www.mdpi.com/2073-8994/12/6/938ultrasound imagingdiscrete wavelet transformweighted guided image filteringgradient domain guided image filteringspeckle noise
collection DOAJ
language English
format Article
sources DOAJ
author Hyunho Choi
Jechang Jeong
spellingShingle Hyunho Choi
Jechang Jeong
Despeckling Algorithm for Removing Speckle Noise from Ultrasound Images
Symmetry
ultrasound imaging
discrete wavelet transform
weighted guided image filtering
gradient domain guided image filtering
speckle noise
author_facet Hyunho Choi
Jechang Jeong
author_sort Hyunho Choi
title Despeckling Algorithm for Removing Speckle Noise from Ultrasound Images
title_short Despeckling Algorithm for Removing Speckle Noise from Ultrasound Images
title_full Despeckling Algorithm for Removing Speckle Noise from Ultrasound Images
title_fullStr Despeckling Algorithm for Removing Speckle Noise from Ultrasound Images
title_full_unstemmed Despeckling Algorithm for Removing Speckle Noise from Ultrasound Images
title_sort despeckling algorithm for removing speckle noise from ultrasound images
publisher MDPI AG
series Symmetry
issn 2073-8994
publishDate 2020-06-01
description Ultrasound (US) imaging can examine human bodies of various ages; however, in the process of obtaining a US image, speckle noise is generated. The speckle noise inhibits physicians from accurately examining lesions; thus, a speckle noise removal method is essential technology. To enhance speckle noise elimination, we propose a novel algorithm using the characteristics of speckle noise and filtering methods based on speckle reducing anisotropic diffusion (SRAD) filtering, discrete wavelet transform (DWT) using symmetry characteristics, weighted guided image filtering (WGIF), and gradient domain guided image filtering (GDGIF). The SRAD filter is exploited as a preprocessing filter because it can be directly applied to a medical US image containing speckle noise without a log-compression. The wavelet domain has the advantage of suppressing the additive noise. Therefore, a homomorphic transformation is utilized to convert the multiplicative noise into additive noise. After two-level DWT decomposition is applied, to suppress the residual noise of an SRAD filtered image, GDGIF and WGIF are exploited to reduce noise from seven high-frequency sub-band images and one low-frequency sub-band image, respectively. Finally, a noise-free image is attained through inverse DWT and an exponential transform. The proposed algorithm exhibits excellent speckle noise elimination and edge conservation as compared with conventional denoising methods.
topic ultrasound imaging
discrete wavelet transform
weighted guided image filtering
gradient domain guided image filtering
speckle noise
url https://www.mdpi.com/2073-8994/12/6/938
work_keys_str_mv AT hyunhochoi despecklingalgorithmforremovingspecklenoisefromultrasoundimages
AT jechangjeong despecklingalgorithmforremovingspecklenoisefromultrasoundimages
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