On the compensation of uneven illumination in retinal images for restoration by means of blind deconvolution

Retinal eye fundus images are used for diagnostic purposes, but despite controlled conditions in acquisition they often suffer from uneven illumination and blur. In this work, we propose the use of multi-channel blind deconvolution for the restoration of blurred retinal images. The estimation of an...

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Tipo de recurso:
Fecha de publicación:
2016
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/8978
Acceso en línea:
https://hdl.handle.net/20.500.12585/8978
Palabra clave:
Blood vessels
Convolution
Medical imaging
Ophthalmology
Optical transfer function
Restoration
Signal processing
Vision
Bi dimensional empirical mode decomposition (BEMD)
Blind deconvolution
Controlled conditions
Illumination compensation
Illumination distribution
Multi channel
Nonstationary signals
Uneven illuminations
Image processing
Rights
restrictedAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
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oai_identifier_str oai:repositorio.utb.edu.co:20.500.12585/8978
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network_name_str Repositorio Institucional UTB
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dc.title.none.fl_str_mv On the compensation of uneven illumination in retinal images for restoration by means of blind deconvolution
title On the compensation of uneven illumination in retinal images for restoration by means of blind deconvolution
spellingShingle On the compensation of uneven illumination in retinal images for restoration by means of blind deconvolution
Blood vessels
Convolution
Medical imaging
Ophthalmology
Optical transfer function
Restoration
Signal processing
Vision
Bi dimensional empirical mode decomposition (BEMD)
Blind deconvolution
Controlled conditions
Illumination compensation
Illumination distribution
Multi channel
Nonstationary signals
Uneven illuminations
Image processing
title_short On the compensation of uneven illumination in retinal images for restoration by means of blind deconvolution
title_full On the compensation of uneven illumination in retinal images for restoration by means of blind deconvolution
title_fullStr On the compensation of uneven illumination in retinal images for restoration by means of blind deconvolution
title_full_unstemmed On the compensation of uneven illumination in retinal images for restoration by means of blind deconvolution
title_sort On the compensation of uneven illumination in retinal images for restoration by means of blind deconvolution
dc.contributor.editor.none.fl_str_mv Altuve M.
dc.subject.keywords.none.fl_str_mv Blood vessels
Convolution
Medical imaging
Ophthalmology
Optical transfer function
Restoration
Signal processing
Vision
Bi dimensional empirical mode decomposition (BEMD)
Blind deconvolution
Controlled conditions
Illumination compensation
Illumination distribution
Multi channel
Nonstationary signals
Uneven illuminations
Image processing
topic Blood vessels
Convolution
Medical imaging
Ophthalmology
Optical transfer function
Restoration
Signal processing
Vision
Bi dimensional empirical mode decomposition (BEMD)
Blind deconvolution
Controlled conditions
Illumination compensation
Illumination distribution
Multi channel
Nonstationary signals
Uneven illuminations
Image processing
description Retinal eye fundus images are used for diagnostic purposes, but despite controlled conditions in acquisition they often suffer from uneven illumination and blur. In this work, we propose the use of multi-channel blind deconvolution for the restoration of blurred retinal images. The estimation of an adequate point-spread function (PSF) is highly dependent on the registration of at least two images from the same retina, which undergo illumination compensation. We use the bi-dimensional empirical mode decomposition (BEMD) approach to model the illumination distribution as a sum of non-stationary signals. The BEMD approach enables an artifact-free compensation of the illumination in order to estimate an adequate PSF and carry out the best restoration possible. Encouraging experimental results show significant enhancement in the retinal images with increased contrast and visibility of subtle details like small blood vessels. © 2016 IEEE.
publishDate 2016
dc.date.issued.none.fl_str_mv 2016
dc.date.accessioned.none.fl_str_mv 2020-03-26T16:32:42Z
dc.date.available.none.fl_str_mv 2020-03-26T16:32:42Z
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status_str publishedVersion
dc.identifier.citation.none.fl_str_mv 2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
dc.identifier.isbn.none.fl_str_mv 9781509037971
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/8978
dc.identifier.doi.none.fl_str_mv 10.1109/STSIVA.2016.7743327
dc.identifier.instname.none.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.none.fl_str_mv Repositorio UTB
dc.identifier.orcid.none.fl_str_mv 24329839300
57117284600
57210822856
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identifier_str_mv 2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
9781509037971
10.1109/STSIVA.2016.7743327
Universidad Tecnológica de Bolívar
Repositorio UTB
24329839300
57117284600
57210822856
7201466399
url https://hdl.handle.net/20.500.12585/8978
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.conferencedate.none.fl_str_mv 30 August 2016 through 2 September 2016
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dc.rights.cc.none.fl_str_mv Atribución-NoComercial 4.0 Internacional
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
Atribución-NoComercial 4.0 Internacional
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dc.format.medium.none.fl_str_mv Recurso electrónico
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
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dc.source.event.none.fl_str_mv 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
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spelling Altuve M.Marrugo A.G.Vargas R.Contreras Ortiz, Sonia HelenaMillan M.S.2020-03-26T16:32:42Z2020-03-26T16:32:42Z20162016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 20169781509037971https://hdl.handle.net/20.500.12585/897810.1109/STSIVA.2016.7743327Universidad Tecnológica de BolívarRepositorio UTB2432983930057117284600572108228567201466399Retinal eye fundus images are used for diagnostic purposes, but despite controlled conditions in acquisition they often suffer from uneven illumination and blur. In this work, we propose the use of multi-channel blind deconvolution for the restoration of blurred retinal images. The estimation of an adequate point-spread function (PSF) is highly dependent on the registration of at least two images from the same retina, which undergo illumination compensation. We use the bi-dimensional empirical mode decomposition (BEMD) approach to model the illumination distribution as a sum of non-stationary signals. The BEMD approach enables an artifact-free compensation of the illumination in order to estimate an adequate PSF and carry out the best restoration possible. Encouraging experimental results show significant enhancement in the retinal images with increased contrast and visibility of subtle details like small blood vessels. © 2016 IEEE.Universidad Pontificia Bolivariana (UPB) Seccional BucaramangaRecurso electrónicoapplication/pdfengInstitute of Electrical and Electronics Engineers Inc.http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85002970865&doi=10.1109%2fSTSIVA.2016.7743327&partnerID=40&md5=f0903522fcb6848666232c0a900c8fc1Scopus2-s2.0-8500297086521st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016On the compensation of uneven illumination in retinal images for restoration by means of blind deconvolutioninfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionConferenciahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fBlood vesselsConvolutionMedical imagingOphthalmologyOptical transfer functionRestorationSignal processingVisionBi dimensional empirical mode decomposition (BEMD)Blind deconvolutionControlled conditionsIllumination compensationIllumination distributionMulti channelNonstationary signalsUneven illuminationsImage processing30 August 2016 through 2 September 2016Akram, M.U., Khitran, S., Usman, A., Yasin, U., Detection of hemorrhages in colored fundus images using non uniform illumination estimation (2014) Lecture Notes in Computer Science, 8815, pp. 329-336. , In A. Campilho and M. Kamel, editors. Springer International PublishingLu, Y., Xie, F., Wu, Y., Jiang, Z., Meng, R., No reference uneven illumination assessment for dermoscopy images (2015) IEEE Signal Processing Letters, 22 (5), pp. 534-538Marrugo, A.G., Millan, M.S., Retinal image analysis oriented to the clinical task (2014) Electronic Letters on Computer Vision and Image Analysis, 13 (2), pp. 54-55Marrugo, A.G., Sorel, M., Sroubek, F., Millan, M.S., Retinal image restoration by means of blind deconvolution (2011) Journal of Biomedical Optics, 16 (11), p. 116016Newton, M.J., The promise of telemedicine (2014) Survey of Ophthalmology, 59 (5), pp. 559-567. , SeptNunes, J.C., Bouaoune, Y., Delechelle, E., Niang, O., Bunel, P., Image analysis by bidimensional empirical mode decomposition (2003) Image and Vision Computing, 21 (12), pp. 1019-1026. , NovSroubek, F., Flusser, J., Multichannel blind deconvolution of spatially misaligned images (2005) IEEE Transactions on Image Processing : A Publication of the IEEE Signal Processing Society, 14 (7), pp. 874-883. , Julyhttp://purl.org/coar/resource_type/c_c94fTHUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/8978/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/8978oai:repositorio.utb.edu.co:20.500.12585/89782023-05-25 15:45:59.429Repositorio Institucional UTBrepositorioutb@utb.edu.co

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