{"id":"https://openalex.org/W2069431347","doi":"https://doi.org/10.1109/icassp.2014.6853947","title":"Entropy based merging of context models for efficient arithmetic coding","display_name":"Entropy based merging of context models for efficient arithmetic coding","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2069431347","doi":"https://doi.org/10.1109/icassp.2014.6853947","mag":"2069431347"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2014.6853947","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6853947","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5002596904","display_name":"Tilo Strutz","orcid":"https://orcid.org/0000-0001-5063-6515"},"institutions":[{"id":"https://openalex.org/I926574661","display_name":"Leipzig University","ror":"https://ror.org/03s7gtk40","country_code":"DE","type":"education","lineage":["https://openalex.org/I926574661"]},{"id":"https://openalex.org/I4210093367","display_name":"Deutsche Telekom (Germany)","ror":"https://ror.org/00m8prc86","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210093367"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Tilo Strutz","raw_affiliation_strings":["Deutsche Telekom, Institute of Communications Engineering, Leipzig, Germany","Inst. of Commun. Eng., Leipzig Univ. of Telecommun., Leipzig, Germany"],"affiliations":[{"raw_affiliation_string":"Deutsche Telekom, Institute of Communications Engineering, Leipzig, Germany","institution_ids":["https://openalex.org/I4210093367"]},{"raw_affiliation_string":"Inst. of Commun. Eng., Leipzig Univ. of Telecommun., Leipzig, Germany","institution_ids":["https://openalex.org/I926574661"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5002596904"],"corresponding_institution_ids":["https://openalex.org/I4210093367","https://openalex.org/I926574661"],"apc_list":null,"apc_paid":null,"fwci":0.4877,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.69982847,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"3","issue":null,"first_page":"1991","last_page":"1995"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9973999857902527,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.991100013256073,"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/lossless-compression","display_name":"Lossless compression","score":0.7774854898452759},{"id":"https://openalex.org/keywords/arithmetic-coding","display_name":"Arithmetic coding","score":0.7716812491416931},{"id":"https://openalex.org/keywords/entropy-encoding","display_name":"Entropy encoding","score":0.7403896450996399},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6938068866729736},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6646283268928528},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5977936387062073},{"id":"https://openalex.org/keywords/tunstall-coding","display_name":"Tunstall coding","score":0.5607624650001526},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5537225604057312},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4853633642196655},{"id":"https://openalex.org/keywords/context-adaptive-binary-arithmetic-coding","display_name":"Context-adaptive binary arithmetic coding","score":0.48188096284866333},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.46399566531181335},{"id":"https://openalex.org/keywords/huffman-coding","display_name":"Huffman coding","score":0.4630683958530426},{"id":"https://openalex.org/keywords/adaptive-coding","display_name":"Adaptive coding","score":0.45184943079948425},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.4384043216705322},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.42402857542037964},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41528043150901794},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.41511741280555725},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3528239130973816},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24355491995811462},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.22126176953315735},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1424858272075653},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10278338193893433}],"concepts":[{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.7774854898452759},{"id":"https://openalex.org/C153338461","wikidata":"https://www.wikidata.org/wiki/Q2651","display_name":"Arithmetic coding","level":4,"score":0.7716812491416931},{"id":"https://openalex.org/C1769480","wikidata":"https://www.wikidata.org/wiki/Q1345239","display_name":"Entropy encoding","level":3,"score":0.7403896450996399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6938068866729736},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6646283268928528},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5977936387062073},{"id":"https://openalex.org/C73231260","wikidata":"https://www.wikidata.org/wiki/Q7853376","display_name":"Tunstall coding","level":4,"score":0.5607624650001526},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5537225604057312},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4853633642196655},{"id":"https://openalex.org/C175732694","wikidata":"https://www.wikidata.org/wiki/Q1128713","display_name":"Context-adaptive binary arithmetic coding","level":3,"score":0.48188096284866333},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.46399566531181335},{"id":"https://openalex.org/C46900642","wikidata":"https://www.wikidata.org/wiki/Q2647","display_name":"Huffman coding","level":3,"score":0.4630683958530426},{"id":"https://openalex.org/C57890076","wikidata":"https://www.wikidata.org/wiki/Q4680725","display_name":"Adaptive coding","level":4,"score":0.45184943079948425},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.4384043216705322},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.42402857542037964},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41528043150901794},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.41511741280555725},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3528239130973816},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24355491995811462},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.22126176953315735},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1424858272075653},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10278338193893433},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2014.6853947","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6853947","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W104269641","https://openalex.org/W1525840521","https://openalex.org/W1548761446","https://openalex.org/W1627886494","https://openalex.org/W1995813870","https://openalex.org/W2008528947","https://openalex.org/W2080620018","https://openalex.org/W2082967074","https://openalex.org/W2096445898","https://openalex.org/W2113704884","https://openalex.org/W2126894943","https://openalex.org/W2130350995","https://openalex.org/W2131499030","https://openalex.org/W2137923603","https://openalex.org/W2140129192","https://openalex.org/W2164051276","https://openalex.org/W2168202799","https://openalex.org/W6604260991","https://openalex.org/W6631408633","https://openalex.org/W6632774801","https://openalex.org/W6684337973"],"related_works":["https://openalex.org/W2156106714","https://openalex.org/W1579872668","https://openalex.org/W4312628177","https://openalex.org/W1994532706","https://openalex.org/W340392727","https://openalex.org/W4297360799","https://openalex.org/W2064300363","https://openalex.org/W1499106570","https://openalex.org/W2096793045","https://openalex.org/W1492899210"],"abstract_inverted_index":{"The":[0],"contextual":[1,46],"coding":[2],"of":[3,15,32,44,67,88],"data":[4],"requires":[5],"in":[6,54,81],"general":[7],"a":[8,20,26,55,78,85],"step":[9],"which":[10,34],"reduces":[11],"the":[12,42,45,73],"vast":[13],"variety":[14],"possible":[16],"contexts":[17],"down":[18],"to":[19,77],"feasible":[21],"number.":[22],"This":[23,50],"paper":[24],"presents":[25],"new":[27],"method":[28,51],"for":[29,57,70,84],"non-uniform":[30],"quantisation":[31],"contexts,":[33],"adaptively":[35],"merges":[36],"adjacent":[37],"intervals":[38],"as":[39,41],"long":[40],"increase":[43],"entropy":[47],"is":[48,52],"negligible.":[49],"incorporated":[53],"framework":[56],"lossless":[58],"image":[59],"compression.":[60],"In":[61],"combination":[62],"with":[63],"an":[64],"automatic":[65],"determination":[66],"model":[68],"sizes":[69],"histogram-tail":[71],"truncation,":[72],"proposed":[74],"approach":[75],"leads":[76],"significant":[79],"gain":[80],"compression":[82],"performance":[83],"wide":[86],"range":[87],"different":[89],"natural":[90],"images.":[91]},"counts_by_year":[{"year":2018,"cited_by_count":3},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
