Progressive Image Compression With Bandelets

Detalhes bibliográficos
Autor(a) principal: Vasuki, A.
Data de Publicação: 2010
Tipo de documento: Artigo
Idioma: eng
Título da fonte: INFOCOMP: Jornal de Ciência da Computação
Texto Completo: https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/319
Resumo: Image compression has emerged as a major research area due to the phenomenal growth of applications that generate, process and transmit images. Image compression can be sequential or progressive. Progressive compression techniques generate an embedded bit stream and the fidelity ofthe reconstruction depends on the number of bits received and decoded. Natural images contain edges, geometry, texture and other discontinuities / details that are oriented in various directions. The state-ofthe-art wavelet transform captures point singularities, but not along surfaces with geometric regularity. The second generation discrete wavelet-bandelet transform is proposed to overcome the drawback of wavelets in higher dimensions and capture the geometry in images. The redundancy in the wavelet transform is removed by bandeletization. The wavelet-bandelet coefficients are quantized and encoded using modified bit plane coding and the results have been compared with the existing bit plane coding and the set partitioning in hierarchical trees algorithm. Bandelets produce superior visual quality in the reconstructed image than wavelets. The parameters used for the evaluation of the algorithm are compression ratio, bits per pixel and peak signal-to-noise ratio.
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spelling Progressive Image Compression With BandeletsImage CompressionProgressiveWaveletsBande letsBit Plane CodingSPIHT.Image compression has emerged as a major research area due to the phenomenal growth of applications that generate, process and transmit images. Image compression can be sequential or progressive. Progressive compression techniques generate an embedded bit stream and the fidelity ofthe reconstruction depends on the number of bits received and decoded. Natural images contain edges, geometry, texture and other discontinuities / details that are oriented in various directions. The state-ofthe-art wavelet transform captures point singularities, but not along surfaces with geometric regularity. The second generation discrete wavelet-bandelet transform is proposed to overcome the drawback of wavelets in higher dimensions and capture the geometry in images. The redundancy in the wavelet transform is removed by bandeletization. The wavelet-bandelet coefficients are quantized and encoded using modified bit plane coding and the results have been compared with the existing bit plane coding and the set partitioning in hierarchical trees algorithm. Bandelets produce superior visual quality in the reconstructed image than wavelets. The parameters used for the evaluation of the algorithm are compression ratio, bits per pixel and peak signal-to-noise ratio.Editora da UFLA2010-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/319INFOCOMP Journal of Computer Science; Vol. 9 No. 4 (2010): December, 2010; 21-271982-33631807-4545reponame:INFOCOMP: Jornal de Ciência da Computaçãoinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/319/304Copyright (c) 2016 INFOCOMP Journal of Computer Scienceinfo:eu-repo/semantics/openAccessVasuki, A.2015-07-29T11:48:16Zoai:infocomp.dcc.ufla.br:article/319Revistahttps://infocomp.dcc.ufla.br/index.php/infocompPUBhttps://infocomp.dcc.ufla.br/index.php/infocomp/oaiinfocomp@dcc.ufla.br||apfreire@dcc.ufla.br1982-33631807-4545opendoar:2024-05-21T19:54:31.753434INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Progressive Image Compression With Bandelets
title Progressive Image Compression With Bandelets
spellingShingle Progressive Image Compression With Bandelets
Vasuki, A.
Image Compression
Progressive
Wavelets
Bande lets
Bit Plane Coding
SPIHT.
title_short Progressive Image Compression With Bandelets
title_full Progressive Image Compression With Bandelets
title_fullStr Progressive Image Compression With Bandelets
title_full_unstemmed Progressive Image Compression With Bandelets
title_sort Progressive Image Compression With Bandelets
author Vasuki, A.
author_facet Vasuki, A.
author_role author
dc.contributor.author.fl_str_mv Vasuki, A.
dc.subject.por.fl_str_mv Image Compression
Progressive
Wavelets
Bande lets
Bit Plane Coding
SPIHT.
topic Image Compression
Progressive
Wavelets
Bande lets
Bit Plane Coding
SPIHT.
description Image compression has emerged as a major research area due to the phenomenal growth of applications that generate, process and transmit images. Image compression can be sequential or progressive. Progressive compression techniques generate an embedded bit stream and the fidelity ofthe reconstruction depends on the number of bits received and decoded. Natural images contain edges, geometry, texture and other discontinuities / details that are oriented in various directions. The state-ofthe-art wavelet transform captures point singularities, but not along surfaces with geometric regularity. The second generation discrete wavelet-bandelet transform is proposed to overcome the drawback of wavelets in higher dimensions and capture the geometry in images. The redundancy in the wavelet transform is removed by bandeletization. The wavelet-bandelet coefficients are quantized and encoded using modified bit plane coding and the results have been compared with the existing bit plane coding and the set partitioning in hierarchical trees algorithm. Bandelets produce superior visual quality in the reconstructed image than wavelets. The parameters used for the evaluation of the algorithm are compression ratio, bits per pixel and peak signal-to-noise ratio.
publishDate 2010
dc.date.none.fl_str_mv 2010-12-01
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 https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/319
url https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/319
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/319/304
dc.rights.driver.fl_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv INFOCOMP Journal of Computer Science; Vol. 9 No. 4 (2010): December, 2010; 21-27
1982-3363
1807-4545
reponame:INFOCOMP: Jornal de Ciência da Computação
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str INFOCOMP: Jornal de Ciência da Computação
collection INFOCOMP: Jornal de Ciência da Computação
repository.name.fl_str_mv INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv infocomp@dcc.ufla.br||apfreire@dcc.ufla.br
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