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Article: Compound document compression with model-based biased reconstruction

TitleCompound document compression with model-based biased reconstruction
Authors
Issue Date2004
PublisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/jei
Citation
Journal Of Electronic Imaging, 2004, v. 13 n. 1, p. 191-197 How to Cite?
AbstractThe usefulness of electronic document delivery and archives rests in large part on advances in compression technology. Documents can contain complex layouts with different data types, such as text and images, having different statistical characteristics. To achieve better image quality, it is important to make use of such characteristics in compression. We exploit the transform coefficient distributions for text and images. We show that the scheme in base-line JPEG does not lead to minimum mean-square error if we have models of these coefficients. Instead, we discuss an algorithm designed for this performance that involves first classifying the blocks, and then estimating the parameters to enable a biased reconstruction in the decompression value. Simulation results are shown to validate the advantages of this method. © 2004 SPIE and IS&T.
Persistent Identifierhttp://hdl.handle.net/10722/42949
ISSN
2015 Impact Factor: 0.616
2015 SCImago Journal Rankings: 0.341
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLam, EYen_HK
dc.date.accessioned2007-03-23T04:35:18Z-
dc.date.available2007-03-23T04:35:18Z-
dc.date.issued2004en_HK
dc.identifier.citationJournal Of Electronic Imaging, 2004, v. 13 n. 1, p. 191-197en_HK
dc.identifier.issn1017-9909en_HK
dc.identifier.urihttp://hdl.handle.net/10722/42949-
dc.description.abstractThe usefulness of electronic document delivery and archives rests in large part on advances in compression technology. Documents can contain complex layouts with different data types, such as text and images, having different statistical characteristics. To achieve better image quality, it is important to make use of such characteristics in compression. We exploit the transform coefficient distributions for text and images. We show that the scheme in base-line JPEG does not lead to minimum mean-square error if we have models of these coefficients. Instead, we discuss an algorithm designed for this performance that involves first classifying the blocks, and then estimating the parameters to enable a biased reconstruction in the decompression value. Simulation results are shown to validate the advantages of this method. © 2004 SPIE and IS&T.en_HK
dc.format.extent500750 bytes-
dc.format.extent25600 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/msword-
dc.languageengen_HK
dc.publisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/jeien_HK
dc.relation.ispartofJournal of Electronic Imagingen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsCopyright 2004 Society of Photo-Optical Instrumentation Engineers. This paper was published in Journal of Electronic Imaging, 2004, v. 13 n. 1, p. 191-197 and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.en_HK
dc.titleCompound document compression with model-based biased reconstructionen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1017-9909&volume=13&issue=1&spage=191&epage=197&date=2004&atitle=Compound+document+compression+with+model-based+biased+reconstructionen_HK
dc.identifier.emailLam, EY:elam@eee.hku.hken_HK
dc.identifier.authorityLam, EY=rp00131en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1117/1.1631317en_HK
dc.identifier.scopuseid_2-s2.0-1842421980en_HK
dc.identifier.hkuros88826-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-1842421980&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume13en_HK
dc.identifier.issue1en_HK
dc.identifier.spage191en_HK
dc.identifier.epage197en_HK
dc.identifier.isiWOS:000220220900021-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLam, EY=7102890004en_HK

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