{"id":"https://openalex.org/W2107617803","doi":"https://doi.org/10.1109/icip.2004.1421794","title":"Multidimensional signal compression using multi-scale recurrent patterns with smooth side-match criterion","display_name":"Multidimensional signal compression using multi-scale recurrent patterns with smooth side-match criterion","publication_year":2005,"publication_date":"2005-04-19","ids":{"openalex":"https://openalex.org/W2107617803","doi":"https://doi.org/10.1109/icip.2004.1421794","mag":"2107617803"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2004.1421794","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2004.1421794","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 International Conference on Image Processing, 2004. ICIP '04.","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114027763","display_name":"Eddie B. L. Filho","orcid":null},"institutions":[{"id":"https://openalex.org/I122140584","display_name":"Universidade Federal do Rio de Janeiro","ror":"https://ror.org/03490as77","country_code":"BR","type":"education","lineage":["https://openalex.org/I122140584"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"E.B.L. Filho","raw_affiliation_strings":["Genius Institute of Technology, AM, BRAZIL","PEE/COPPE/DEL/POLI, Universidade Federal do Rio de, Rio de Janeiro, RJ, BRAZIL","Genius Inst. of Technol., Brazil"],"affiliations":[{"raw_affiliation_string":"Genius Institute of Technology, AM, BRAZIL","institution_ids":[]},{"raw_affiliation_string":"PEE/COPPE/DEL/POLI, Universidade Federal do Rio de, Rio de Janeiro, RJ, BRAZIL","institution_ids":["https://openalex.org/I122140584"]},{"raw_affiliation_string":"Genius Inst. of Technol., Brazil","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073008665","display_name":"Murilo B. de Carvalho","orcid":"https://orcid.org/0000-0002-7964-1876"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M.B. de Carvalho","raw_affiliation_strings":["federal fluminense university"],"affiliations":[{"raw_affiliation_string":"federal fluminense university","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081219742","display_name":"Eduardo A. B. da Silva","orcid":"https://orcid.org/0000-0001-7755-6988"},"institutions":[{"id":"https://openalex.org/I122140584","display_name":"Universidade Federal do Rio de Janeiro","ror":"https://ror.org/03490as77","country_code":"BR","type":"education","lineage":["https://openalex.org/I122140584"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"E.A.B. da Silva","raw_affiliation_strings":["PEE/COPPE/DEL/POLI, Universidade Federal do Rio de, Rio de Janeiro, RJ, BRAZIL","Universidade Federal do Rio de Janeiro"],"affiliations":[{"raw_affiliation_string":"PEE/COPPE/DEL/POLI, Universidade Federal do Rio de, Rio de Janeiro, RJ, BRAZIL","institution_ids":["https://openalex.org/I122140584"]},{"raw_affiliation_string":"Universidade Federal do Rio de Janeiro","institution_ids":["https://openalex.org/I122140584"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5114027763"],"corresponding_institution_ids":["https://openalex.org/I122140584"],"apc_list":null,"apc_paid":null,"fwci":2.0892,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.88244692,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":null,"first_page":"3201","last_page":"3204"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9842000007629395,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7522485256195068},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.5856626629829407},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.5778096914291382},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.5550850033760071},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5386348366737366},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46640506386756897},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.4473435878753662},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4409267008304596},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4331872761249542},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.34782522916793823},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33143728971481323},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.206478089094162}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7522485256195068},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.5856626629829407},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.5778096914291382},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.5550850033760071},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5386348366737366},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46640506386756897},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.4473435878753662},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4409267008304596},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4331872761249542},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.34782522916793823},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33143728971481323},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.206478089094162}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2004.1421794","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2004.1421794","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 International Conference on Image Processing, 2004. ICIP '04.","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.133.6051","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.133.6051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.lps.ufrj.br/profs/eduardo/papers/ci46.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2111437534","https://openalex.org/W2113111118","https://openalex.org/W2118217749","https://openalex.org/W2142276208","https://openalex.org/W2151996674","https://openalex.org/W4302366751"],"related_works":["https://openalex.org/W115686965","https://openalex.org/W2768918307","https://openalex.org/W2110031805","https://openalex.org/W2040020606","https://openalex.org/W4362659915","https://openalex.org/W2113071088","https://openalex.org/W2116526828","https://openalex.org/W2094714038","https://openalex.org/W2144404403","https://openalex.org/W2093548240"],"abstract_inverted_index":{"The":[0,96],"recently":[1],"proposed":[2,170],"method":[3,171],"for":[4,23,30,39,61,157,186,198],"image":[5],"compression":[6],"based":[7],"on":[8],"multi-scale":[9],"recurrent":[10],"patterns,":[11],"the":[12,49,52,63,101,122,134,146,149,169,177,183,191,195],"MMP":[13,147,185,197],"(multidimensional":[14],"multiscale":[15],"parser)":[16],"has":[17],"been":[18],"shown":[19],"to":[20,133,142],"perform":[21,143],"well":[22],"a":[24,73,94],"large":[25],"class":[26],"of":[27,51,91,108,113,176,179,194],"images,":[28,188],"specially":[29],"those":[31],"containing":[32,159],"text":[33,160,200],"or":[34,161],"graphics.":[35,162],"However,":[36,117],"its":[37,155],"performance":[38,156,193],"coding":[40],"smooth,":[41,152],"gray":[42],"scale":[43],"images":[44,150,158],"is":[45,76,85,98,103,172],"still":[46],"distant":[47],"from":[48],"state":[50],"art.":[53],"In":[54,67],"this":[55,68],"paper":[56],"we":[57],"propose":[58],"an":[59],"extension":[60],"it,":[62],"SM-MMP":[64,121],"(side-match":[65],"MMP).":[66],"method,":[69],"as":[70],"in":[71,93,120],"MMP,":[72,119],"multidimensional":[74],"signal":[75],"recursively":[77],"segmented":[78],"into":[79],"variable-length":[80],"blocks,":[81],"and":[82,89,110,201],"each":[83],"segment":[84],"encoded":[86,115],"using":[87,106],"expansions":[88],"contractions":[90],"vectors":[92],"dictionary.":[95],"dictionary":[97],"updated":[99],"while":[100,189],"data":[102],"being":[104],"encoded,":[105],"concatenations":[107],"expanded":[109],"contracted":[111],"versions":[112],"previously":[114],"blocks.":[116],"unlike":[118],"dictionaries":[123],"are":[124,151],"built":[125],"considering":[126],"smoothness":[127],"constraints":[128],"around":[129],"block":[130],"boundaries,":[131],"similar":[132],"side-match":[135],"vector":[136],"quantization":[137],"methods.":[138],"This":[139],"allows":[140],"it":[141],"better":[144],"than":[145],"when":[148],"without":[153],"sacrificing":[154],"Indeed,":[163],"our":[164],"simulation":[165],"results":[166],"show":[167],"that":[168],"effective,":[173],"yielding":[174],"improvements":[175],"order":[178],"1.5":[180],"dB":[181],"over":[182],"original":[184,196],"grayscale":[187],"preserving":[190],"high":[192],"graphics,":[199],"mixed":[202],"images.":[203]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}