Progressive Image Compression With Bandelets
Autor(a) principal: | |
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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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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 |
_version_ |
1799874741359607808 |