A survey on palette reordering methods for improving the compression of color-indexed images.
Identifieur interne : 000395 ( Ncbi/Merge ); précédent : 000394; suivant : 000396A survey on palette reordering methods for improving the compression of color-indexed images.
Auteurs : Armando J. Pinho [Portugal] ; Ant Nio J R. NevesSource :
- IEEE transactions on image processing : a publication of the IEEE Signal Processing Society [ 1057-7149 ] ; 2004.
Descripteurs français
- KwdFr :
- Algorithmes, Amélioration d'image (), Analyse de regroupements, Analyse numérique assistée par ordinateur, Compression de données (), Couleur, Hypermédia, Infographie, Intelligence artificielle, Interprétation d'image assistée par ordinateur (), Reconnaissance automatique des formes (), Reproductibilité des résultats, Sensibilité et spécificité, Traitement du signal assisté par ordinateur.
- MESH :
- Algorithmes, Amélioration d'image, Analyse de regroupements, Analyse numérique assistée par ordinateur, Compression de données, Couleur, Hypermédia, Infographie, Intelligence artificielle, Interprétation d'image assistée par ordinateur, Reconnaissance automatique des formes, Reproductibilité des résultats, Sensibilité et spécificité, Traitement du signal assisté par ordinateur.
English descriptors
- KwdEn :
- Algorithms, Artificial Intelligence, Cluster Analysis, Color, Computer Graphics, Data Compression (methods), Hypermedia, Image Enhancement (methods), Image Interpretation, Computer-Assisted (methods), Numerical Analysis, Computer-Assisted, Pattern Recognition, Automated (methods), Reproducibility of Results, Sensitivity and Specificity, Signal Processing, Computer-Assisted.
- MESH :
- methods : Data Compression, Image Enhancement, Image Interpretation, Computer-Assisted, Pattern Recognition, Automated.
- Algorithms, Artificial Intelligence, Cluster Analysis, Color, Computer Graphics, Hypermedia, Numerical Analysis, Computer-Assisted, Reproducibility of Results, Sensitivity and Specificity, Signal Processing, Computer-Assisted.
Abstract
Palette reordering is a well-known and very effective approach for improving the compression of color-indexed images. In this paper, we provide a survey of palette reordering methods, and we give experimental results comparing the ability of seven of them in improving the compression efficiency of JPEG-LS and lossless JPEG 2000. We concluded that the pairwise merging heuristic proposed by Memon et al. is the most effective, but also the most computationally demanding. Moreover, we found that the second most effective method is a modified version of Zeng's reordering technique, which was 3%-5% worse than pairwise merging, but much faster.
PubMed: 15540450
Links toward previous steps (curation, corpus...)
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Links to Exploration step
pubmed:15540450Le document en format XML
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Neves</name></author></analytic><series><title level="j">IEEE transactions on image processing : a publication of the IEEE Signal Processing Society</title><idno type="ISSN">1057-7149</idno><imprint><date when="2004" type="published">2004</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Artificial Intelligence</term><term>Cluster Analysis</term><term>Color</term><term>Computer Graphics</term><term>Data Compression (methods)</term><term>Hypermedia</term><term>Image Enhancement (methods)</term><term>Image Interpretation, Computer-Assisted (methods)</term><term>Numerical Analysis, Computer-Assisted</term><term>Pattern Recognition, Automated (methods)</term><term>Reproducibility of Results</term><term>Sensitivity and Specificity</term><term>Signal Processing, Computer-Assisted</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Amélioration d'image ()</term><term>Analyse de regroupements</term><term>Analyse numérique assistée par ordinateur</term><term>Compression de données ()</term><term>Couleur</term><term>Hypermédia</term><term>Infographie</term><term>Intelligence artificielle</term><term>Interprétation d'image assistée par ordinateur ()</term><term>Reconnaissance automatique des formes ()</term><term>Reproductibilité des résultats</term><term>Sensibilité et spécificité</term><term>Traitement du signal assisté par ordinateur</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Data Compression</term><term>Image Enhancement</term><term>Image Interpretation, Computer-Assisted</term><term>Pattern Recognition, Automated</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Artificial Intelligence</term><term>Cluster Analysis</term><term>Color</term><term>Computer Graphics</term><term>Hypermedia</term><term>Numerical Analysis, Computer-Assisted</term><term>Reproducibility of Results</term><term>Sensitivity and Specificity</term><term>Signal Processing, Computer-Assisted</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Amélioration d'image</term><term>Analyse de regroupements</term><term>Analyse numérique assistée par ordinateur</term><term>Compression de données</term><term>Couleur</term><term>Hypermédia</term><term>Infographie</term><term>Intelligence artificielle</term><term>Interprétation d'image assistée par ordinateur</term><term>Reconnaissance automatique des formes</term><term>Reproductibilité des résultats</term><term>Sensibilité et spécificité</term><term>Traitement du signal assisté par ordinateur</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Palette reordering is a well-known and very effective approach for improving the compression of color-indexed images. In this paper, we provide a survey of palette reordering methods, and we give experimental results comparing the ability of seven of them in improving the compression efficiency of JPEG-LS and lossless JPEG 2000. We concluded that the pairwise merging heuristic proposed by Memon et al. is the most effective, but also the most computationally demanding. Moreover, we found that the second most effective method is a modified version of Zeng's reordering technique, which was 3%-5% worse than pairwise merging, but much faster.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">15540450</PMID><DateCreated><Year>2004</Year><Month>11</Month><Day>15</Day></DateCreated><DateCompleted><Year>2004</Year><Month>12</Month><Day>08</Day></DateCompleted><DateRevised><Year>2006</Year><Month>11</Month><Day>15</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">1057-7149</ISSN><JournalIssue CitedMedium="Print"><Volume>13</Volume><Issue>11</Issue><PubDate><Year>2004</Year><Month>Nov</Month></PubDate></JournalIssue><Title>IEEE transactions on image processing : a publication of the IEEE Signal Processing Society</Title><ISOAbbreviation>IEEE Trans Image Process</ISOAbbreviation></Journal><ArticleTitle>A survey on palette reordering methods for improving the compression of color-indexed images.</ArticleTitle><Pagination><MedlinePgn>1411-8</MedlinePgn></Pagination><Abstract><AbstractText>Palette reordering is a well-known and very effective approach for improving the compression of color-indexed images. In this paper, we provide a survey of palette reordering methods, and we give experimental results comparing the ability of seven of them in improving the compression efficiency of JPEG-LS and lossless JPEG 2000. We concluded that the pairwise merging heuristic proposed by Memon et al. is the most effective, but also the most computationally demanding. 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Neves</name></noCountry><country name="Portugal"><noRegion><name sortKey="Pinho, Armando J" sort="Pinho, Armando J" uniqKey="Pinho A" first="Armando J" last="Pinho">Armando J. Pinho</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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