An algorithm for compression of bilevel images
This paper presents the block arithmetic coding for image compression (BACIC) algorithm: a new method for lossless bilevel image compression which can replace JBIG, the current standard for bilevel image compression. BACIC uses the block arithmetic coder (BAC): a simple, efficient, easy-to-implement...
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Veröffentlicht in: | IEEE transactions on image processing 2001-05, Vol.10 (5), p.669-676 |
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description | This paper presents the block arithmetic coding for image compression (BACIC) algorithm: a new method for lossless bilevel image compression which can replace JBIG, the current standard for bilevel image compression. BACIC uses the block arithmetic coder (BAC): a simple, efficient, easy-to-implement, variable-to-fixed arithmetic coder, to encode images. BACIC models its probability estimates adaptively based on a 12-bit context of previous pixel values; the 12-bit context serves as an index into a probability table whose entries are used to compute p/sub 1/ (the probability of a bit equaling one), the probability measure BAC needs to compute a codeword. In contrast, the Joint Bilevel Image Experts Group (JBIG) uses a patented arithmetic coder, the IBM QM-coder, to compress image data and a predetermined probability table to estimate its probability measures. JBIG, though, has not get been commercially implemented; instead, JBIG's predecessor, the Group 3 fax (G3), continues to be used. BACIC achieves compression ratios comparable to JBIG's and is introduced as an alternative to the JBIG and G3 algorithms. BACIC's overall compression ratio is 19.0 for the eight CCITT test images (compared to JBIG's 19.6 and G3's 7.7), is 16.0 for 20 additional business-type documents (compared to JBIG's 16.0 and G3's 6.74), and is 3.07 for halftone images (compared to JBIG's 2.75 and G3's 0.50). |
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BACIC uses the block arithmetic coder (BAC): a simple, efficient, easy-to-implement, variable-to-fixed arithmetic coder, to encode images. BACIC models its probability estimates adaptively based on a 12-bit context of previous pixel values; the 12-bit context serves as an index into a probability table whose entries are used to compute p/sub 1/ (the probability of a bit equaling one), the probability measure BAC needs to compute a codeword. In contrast, the Joint Bilevel Image Experts Group (JBIG) uses a patented arithmetic coder, the IBM QM-coder, to compress image data and a predetermined probability table to estimate its probability measures. JBIG, though, has not get been commercially implemented; instead, JBIG's predecessor, the Group 3 fax (G3), continues to be used. BACIC achieves compression ratios comparable to JBIG's and is introduced as an alternative to the JBIG and G3 algorithms. BACIC's overall compression ratio is 19.0 for the eight CCITT test images (compared to JBIG's 19.6 and G3's 7.7), is 16.0 for 20 additional business-type documents (compared to JBIG's 16.0 and G3's 6.74), and is 3.07 for halftone images (compared to JBIG's 2.75 and G3's 0.50).</description><identifier>ISSN: 1057-7149</identifier><identifier>EISSN: 1941-0042</identifier><identifier>DOI: 10.1109/83.918560</identifier><identifier>PMID: 18249657</identifier><identifier>CODEN: IIPRE4</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Adaptive equalizers ; Algorithms ; Applied sciences ; Arithmetic ; Artificial intelligence ; Business ; Coders ; Computer science; control theory; systems ; Context modeling ; Data compression ; Estimates ; Exact sciences and technology ; Facsimile ; Helium ; Image coding ; Image compression ; Image contrast ; Image processing ; Information, signal and communications theory ; Laboratories ; Mathematical models ; Pattern recognition. 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(IEEE) 2001</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c450t-537c5130559e97d26b3bb2904f6b879ada31b0c638fd075d3c4f7649510c63663</citedby><cites>FETCH-LOGICAL-c450t-537c5130559e97d26b3bb2904f6b879ada31b0c638fd075d3c4f7649510c63663</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/918560$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/918560$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=955780$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18249657$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Reavy, M.D.</creatorcontrib><creatorcontrib>Boncelet, C.G.</creatorcontrib><title>An algorithm for compression of bilevel images</title><title>IEEE transactions on image processing</title><addtitle>TIP</addtitle><addtitle>IEEE Trans Image Process</addtitle><description>This paper presents the block arithmetic coding for image compression (BACIC) algorithm: a new method for lossless bilevel image compression which can replace JBIG, the current standard for bilevel image compression. BACIC uses the block arithmetic coder (BAC): a simple, efficient, easy-to-implement, variable-to-fixed arithmetic coder, to encode images. BACIC models its probability estimates adaptively based on a 12-bit context of previous pixel values; the 12-bit context serves as an index into a probability table whose entries are used to compute p/sub 1/ (the probability of a bit equaling one), the probability measure BAC needs to compute a codeword. In contrast, the Joint Bilevel Image Experts Group (JBIG) uses a patented arithmetic coder, the IBM QM-coder, to compress image data and a predetermined probability table to estimate its probability measures. JBIG, though, has not get been commercially implemented; instead, JBIG's predecessor, the Group 3 fax (G3), continues to be used. BACIC achieves compression ratios comparable to JBIG's and is introduced as an alternative to the JBIG and G3 algorithms. BACIC's overall compression ratio is 19.0 for the eight CCITT test images (compared to JBIG's 19.6 and G3's 7.7), is 16.0 for 20 additional business-type documents (compared to JBIG's 16.0 and G3's 6.74), and is 3.07 for halftone images (compared to JBIG's 2.75 and G3's 0.50).</description><subject>Adaptive equalizers</subject><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Arithmetic</subject><subject>Artificial intelligence</subject><subject>Business</subject><subject>Coders</subject><subject>Computer science; control theory; systems</subject><subject>Context modeling</subject><subject>Data compression</subject><subject>Estimates</subject><subject>Exact sciences and technology</subject><subject>Facsimile</subject><subject>Helium</subject><subject>Image coding</subject><subject>Image compression</subject><subject>Image contrast</subject><subject>Image processing</subject><subject>Information, signal and communications theory</subject><subject>Laboratories</subject><subject>Mathematical models</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Pixel</subject><subject>Signal processing</subject><subject>Studies</subject><subject>Telecommunications and information theory</subject><subject>Testing</subject><issn>1057-7149</issn><issn>1941-0042</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2001</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqF0UtLxDAUBeAgiu-FWxdSFBQXHW-am9dyEF8w4EbXJU1TrbTNmMwI_nszdFBwoauE3I8bOIeQIwoTSkFfKTbRVHEBG2SXaqQ5ABab6Q5c5pKi3iF7Mb4BUORUbJMdqgrUgstdMpkOmelefGgXr33W-JBZ38-Di7H1Q-abrGo79-G6rO3Ni4sHZKsxXXSH63OfPN_ePF3f57PHu4fr6Sy3yGGRcyYtpww4107LuhAVq6pCAzaiUlKb2jBagRVMNTVIXjOLjRSoOV09CsH2ycW4dx78-9LFRdm30bquM4Pzy1hqioIDwv9SMkzRSCiSPP9TFgoZIOf_Q6EYgqYJnv6Cb34ZhhRMqRSKAoXQCV2OyAYfY3BNOQ8pzPBZUihX9ZWKlWN9yZ6sFy6r3tU_ct1XAmdrYKI1XRPMYNv47TTnUq3WHI-qdc79DMc_vgCOVqT2</recordid><startdate>20010501</startdate><enddate>20010501</enddate><creator>Reavy, M.D.</creator><creator>Boncelet, C.G.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Computational geometry</topic><topic>Pixel</topic><topic>Signal processing</topic><topic>Studies</topic><topic>Telecommunications and information theory</topic><topic>Testing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Reavy, M.D.</creatorcontrib><creatorcontrib>Boncelet, C.G.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on image processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Reavy, M.D.</au><au>Boncelet, C.G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An algorithm for compression of bilevel images</atitle><jtitle>IEEE transactions on image processing</jtitle><stitle>TIP</stitle><addtitle>IEEE Trans Image Process</addtitle><date>2001-05-01</date><risdate>2001</risdate><volume>10</volume><issue>5</issue><spage>669</spage><epage>676</epage><pages>669-676</pages><issn>1057-7149</issn><eissn>1941-0042</eissn><coden>IIPRE4</coden><abstract>This paper presents the block arithmetic coding for image compression (BACIC) algorithm: a new method for lossless bilevel image compression which can replace JBIG, the current standard for bilevel image compression. 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subjects | Adaptive equalizers Algorithms Applied sciences Arithmetic Artificial intelligence Business Coders Computer science control theory systems Context modeling Data compression Estimates Exact sciences and technology Facsimile Helium Image coding Image compression Image contrast Image processing Information, signal and communications theory Laboratories Mathematical models Pattern recognition. Digital image processing. Computational geometry Pixel Signal processing Studies Telecommunications and information theory Testing |
title | An algorithm for compression of bilevel images |
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