Constrained PDF based histogram equalization for image constrast enhancement

Detalhes bibliográficos
Autor(a) principal: Balasubramanian, K.
Data de Publicação: 2008
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/15035
Resumo: Histogram Equalization (HE) has proved to be a simple image contrast enhancement technique. However, it tends to change the mean brightness of the image to the middle level of the gray level range. In this paper, a smart contrast enhancement technique based on conventional HE algorithm is proposed. This Constrained PDF based Histogram Equalization (CPHE) technique takes control over the effect of traditional HE so that it performs the enhancement of an image without making any loss of details in it. In the proposed method, the probability distribution function (histogram) of an image is modified by introducing constraints before the histogram equalization (HE) is performed. This shows that such an approach provides a convenient and effective mechanism to control the enhancement process, while being adaptive to various types of images. Experimental results are presented and compared with results from other contemporary methods.
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spelling Constrained PDF based histogram equalization for image constrast enhancementContrast enhancementHistogram equalization (HE)Probability density functionCummulative distribution functionHistogram Equalization (HE) has proved to be a simple image contrast enhancement technique. However, it tends to change the mean brightness of the image to the middle level of the gray level range. In this paper, a smart contrast enhancement technique based on conventional HE algorithm is proposed. This Constrained PDF based Histogram Equalization (CPHE) technique takes control over the effect of traditional HE so that it performs the enhancement of an image without making any loss of details in it. In the proposed method, the probability distribution function (histogram) of an image is modified by introducing constraints before the histogram equalization (HE) is performed. This shows that such an approach provides a convenient and effective mechanism to control the enhancement process, while being adaptive to various types of images. Experimental results are presented and compared with results from other contemporary methods.Universidade Federal de Lavras (UFLA)2008-12-012017-08-01T21:08:49Z2017-08-01T21:08:49Z2017-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfBALASUBRAMANIAN, K. Constrained PDF based histogram equalization for image constrast enhancement. INFOCOMP Journal of Computer Science, Lavras, v. 7, n. 4, p. 78-83, Dec. 2008.http://repositorio.ufla.br/jspui/handle/1/15035INFOCOMP; Vol 7 No 4 (2008): December, 2008; 78-831982-33631807-4545reponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttp://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/241/226Copyright (c) 2016 INFOCOMP Journal of Computer ScienceAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessBalasubramanian, K.2021-09-06T23:41:12Zoai:localhost:1/15035Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2021-09-06T23:41:12Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Constrained PDF based histogram equalization for image constrast enhancement
title Constrained PDF based histogram equalization for image constrast enhancement
spellingShingle Constrained PDF based histogram equalization for image constrast enhancement
Balasubramanian, K.
Contrast enhancement
Histogram equalization (HE)
Probability density function
Cummulative distribution function
title_short Constrained PDF based histogram equalization for image constrast enhancement
title_full Constrained PDF based histogram equalization for image constrast enhancement
title_fullStr Constrained PDF based histogram equalization for image constrast enhancement
title_full_unstemmed Constrained PDF based histogram equalization for image constrast enhancement
title_sort Constrained PDF based histogram equalization for image constrast enhancement
author Balasubramanian, K.
author_facet Balasubramanian, K.
author_role author
dc.contributor.author.fl_str_mv Balasubramanian, K.
dc.subject.por.fl_str_mv Contrast enhancement
Histogram equalization (HE)
Probability density function
Cummulative distribution function
topic Contrast enhancement
Histogram equalization (HE)
Probability density function
Cummulative distribution function
description Histogram Equalization (HE) has proved to be a simple image contrast enhancement technique. However, it tends to change the mean brightness of the image to the middle level of the gray level range. In this paper, a smart contrast enhancement technique based on conventional HE algorithm is proposed. This Constrained PDF based Histogram Equalization (CPHE) technique takes control over the effect of traditional HE so that it performs the enhancement of an image without making any loss of details in it. In the proposed method, the probability distribution function (histogram) of an image is modified by introducing constraints before the histogram equalization (HE) is performed. This shows that such an approach provides a convenient and effective mechanism to control the enhancement process, while being adaptive to various types of images. Experimental results are presented and compared with results from other contemporary methods.
publishDate 2008
dc.date.none.fl_str_mv 2008-12-01
2017-08-01T21:08:49Z
2017-08-01T21:08:49Z
2017-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv BALASUBRAMANIAN, K. Constrained PDF based histogram equalization for image constrast enhancement. INFOCOMP Journal of Computer Science, Lavras, v. 7, n. 4, p. 78-83, Dec. 2008.
http://repositorio.ufla.br/jspui/handle/1/15035
identifier_str_mv BALASUBRAMANIAN, K. Constrained PDF based histogram equalization for image constrast enhancement. INFOCOMP Journal of Computer Science, Lavras, v. 7, n. 4, p. 78-83, Dec. 2008.
url http://repositorio.ufla.br/jspui/handle/1/15035
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/241/226
dc.rights.driver.fl_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Lavras (UFLA)
publisher.none.fl_str_mv Universidade Federal de Lavras (UFLA)
dc.source.none.fl_str_mv INFOCOMP; Vol 7 No 4 (2008): December, 2008; 78-83
1982-3363
1807-4545
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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