Denoising methods for retinal fundus images

Diagnosing retinal diseases of the eye requires analysing tiny retinal vessels. Digital colour fundus images are plagued by the problem of low and varied contrast. Further, with noise being present in the images, retinal vasculature is difficult to be analysed. This paper discusses various denoising...

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Main Authors: Hani, A.F.M., Soomro, T.A., Faye, I., Kamel, N., Yahya, N.
Format: Conference or Workshop Item
Published: IEEE Computer Society 2014
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906335959&doi=10.1109%2fICIAS.2014.6869534&partnerID=40&md5=2e22ac1df3f69588f9cbe96b81441eef
http://eprints.utp.edu.my/32150/
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spelling my.utp.eprints.321502022-03-29T05:00:30Z Denoising methods for retinal fundus images Hani, A.F.M. Soomro, T.A. Faye, I. Kamel, N. Yahya, N. Diagnosing retinal diseases of the eye requires analysing tiny retinal vessels. Digital colour fundus images are plagued by the problem of low and varied contrast. Further, with noise being present in the images, retinal vasculature is difficult to be analysed. This paper discusses various denoising methods to improve the SNR of the retinal fundus images before further image enhancement. By selecting a suitable method for denoising, the image's details are not lost as well as the contrast is maintained. Based on the performance of several techniques for denoising fundus images, it was found that the Time Domain Constraint Estimator (TDCE) showed a greater performance in the PSNR improvement of retinal fundus images. By reducing noise using TDCE, the performance of non-invasive methods for enhancing fundus images can be significantly improved without any loss of the details of the images. © 2014 IEEE. IEEE Computer Society 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906335959&doi=10.1109%2fICIAS.2014.6869534&partnerID=40&md5=2e22ac1df3f69588f9cbe96b81441eef Hani, A.F.M. and Soomro, T.A. and Faye, I. and Kamel, N. and Yahya, N. (2014) Denoising methods for retinal fundus images. In: UNSPECIFIED. http://eprints.utp.edu.my/32150/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Diagnosing retinal diseases of the eye requires analysing tiny retinal vessels. Digital colour fundus images are plagued by the problem of low and varied contrast. Further, with noise being present in the images, retinal vasculature is difficult to be analysed. This paper discusses various denoising methods to improve the SNR of the retinal fundus images before further image enhancement. By selecting a suitable method for denoising, the image's details are not lost as well as the contrast is maintained. Based on the performance of several techniques for denoising fundus images, it was found that the Time Domain Constraint Estimator (TDCE) showed a greater performance in the PSNR improvement of retinal fundus images. By reducing noise using TDCE, the performance of non-invasive methods for enhancing fundus images can be significantly improved without any loss of the details of the images. © 2014 IEEE.
format Conference or Workshop Item
author Hani, A.F.M.
Soomro, T.A.
Faye, I.
Kamel, N.
Yahya, N.
spellingShingle Hani, A.F.M.
Soomro, T.A.
Faye, I.
Kamel, N.
Yahya, N.
Denoising methods for retinal fundus images
author_facet Hani, A.F.M.
Soomro, T.A.
Faye, I.
Kamel, N.
Yahya, N.
author_sort Hani, A.F.M.
title Denoising methods for retinal fundus images
title_short Denoising methods for retinal fundus images
title_full Denoising methods for retinal fundus images
title_fullStr Denoising methods for retinal fundus images
title_full_unstemmed Denoising methods for retinal fundus images
title_sort denoising methods for retinal fundus images
publisher IEEE Computer Society
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906335959&doi=10.1109%2fICIAS.2014.6869534&partnerID=40&md5=2e22ac1df3f69588f9cbe96b81441eef
http://eprints.utp.edu.my/32150/
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