eprintid: 3285
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/32/85
datestamp: 2023-11-09 15:51:33
lastmod: 2023-11-09 15:51:33
status_changed: 2023-11-09 15:46:29
type: conference_item
metadata_visibility: show
creators_name: Hani, A.F.M.
creators_name: Soomro, T.A.
creators_name: Fayee, I.
creators_name: Kamel, N.
creators_name: Yahya, N.
title: Identification of noise in the fundus images
ispublished: pub
note: cited By 14; Conference of 2013 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2013 ; Conference Date: 29 November 2013 Through 1 December 2013; Conference Code:102703
abstract: Analysis of the tiny retinal vasculatures in retinal fundus images becomes difficult due to very low and varied contrast between the retinal vasculature and the background. Fundus fluorescein angiogram overcomes these problems and provides an excellent visualization of the retinal vasculature; however it is an invasive procedure requiring injection of contrasting agents. Further investigation of the RETICA method, a non-invasive method of image enhancement developed earlier, is reported in this paper. It was found that noise is present in the Retinex image. Thus, the identification of the noise in the Retinex image and its removal has been the focus of this research paper. The method used to identify noise is based on adaptive wiener filters (additive, multiplicative, and additive plus multiplicative filters) and the fundus model image and real fundus images are applied to these filters. It is observed that retinal fundus images contained both additive and multiplicative noise. The noise is reduced by using adaptive wiener filter (additive plus multiplicative adaptive wiener filter) based method which resulted in 2.84db an improvement in PSNR. © 2013 IEEE.
date: 2013
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894146772&doi=10.1109%2fICCSCE.2013.6719957&partnerID=40&md5=a3a2bb163f505bf8a005421314121436
id_number: 10.1109/ICCSCE.2013.6719957
full_text_status: none
publication: Proceedings - 2013 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2013
place_of_pub: Penang
pagerange: 191-196
refereed: TRUE
isbn: 9781479915088
citation:   Hani, A.F.M. and Soomro, T.A. and Fayee, I. and Kamel, N. and Yahya, N.  (2013) Identification of noise in the fundus images.  In: UNSPECIFIED.