{"id":"https://openalex.org/W2153107790","doi":"https://doi.org/10.1109/tcom.1985.1096238","title":"Predictive Vector Quantization of Images","display_name":"Predictive Vector Quantization of Images","publication_year":1985,"publication_date":"1985-11-01","ids":{"openalex":"https://openalex.org/W2153107790","doi":"https://doi.org/10.1109/tcom.1985.1096238","mag":"2153107790"},"language":"en","primary_location":{"id":"doi:10.1109/tcom.1985.1096238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcom.1985.1096238","pdf_url":null,"source":{"id":"https://openalex.org/S4210170832","display_name":"IRE Transactions on Communications Systems","issn_l":"0096-2244","issn":["0096-2244","2162-2132"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Communications","raw_type":"journal-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/A5033363752","display_name":"Hsueh\u2010Ming Hang","orcid":"https://orcid.org/0000-0001-8965-2619"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]},{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hsueh-Ming Hang","raw_affiliation_strings":["AT and T Bell Laboratories, Inc., Holmdel, NJ, USA","Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA"],"affiliations":[{"raw_affiliation_string":"AT and T Bell Laboratories, Inc., Holmdel, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109049985","display_name":"J. Woods","orcid":null},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Woods","raw_affiliation_strings":["Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA","institution_ids":["https://openalex.org/I165799507"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033363752"],"corresponding_institution_ids":["https://openalex.org/I1283103587","https://openalex.org/I165799507"],"apc_list":null,"apc_paid":null,"fwci":2.0433,"has_fulltext":false,"cited_by_count":97,"citation_normalized_percentile":{"value":0.8777157,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"33","issue":"11","first_page":"1208","last_page":"1219"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9983000159263611,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9970999956130981,"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/vector-quantization","display_name":"Vector quantization","score":0.8313409090042114},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6628520488739014},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5778781175613403},{"id":"https://openalex.org/keywords/predictive-coding","display_name":"Predictive coding","score":0.5150201320648193},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47921162843704224},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.47648876905441284},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4740421772003174},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46258780360221863},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.45068565011024475},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4485704004764557},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26397353410720825}],"concepts":[{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.8313409090042114},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6628520488739014},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5778781175613403},{"id":"https://openalex.org/C2778061373","wikidata":"https://www.wikidata.org/wiki/Q1315146","display_name":"Predictive coding","level":3,"score":0.5150201320648193},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47921162843704224},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.47648876905441284},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4740421772003174},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46258780360221863},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.45068565011024475},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4485704004764557},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26397353410720825},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcom.1985.1096238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcom.1985.1096238","pdf_url":null,"source":{"id":"https://openalex.org/S4210170832","display_name":"IRE Transactions on Communications Systems","issn_l":"0096-2244","issn":["0096-2244","2162-2132"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Communications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W634924327","https://openalex.org/W1486071255","https://openalex.org/W1940433659","https://openalex.org/W1965565710","https://openalex.org/W1984034733","https://openalex.org/W1990992471","https://openalex.org/W1996771959","https://openalex.org/W2009661248","https://openalex.org/W2058075673","https://openalex.org/W2068903703","https://openalex.org/W2078498116","https://openalex.org/W2089140595","https://openalex.org/W2093440343","https://openalex.org/W2114283721","https://openalex.org/W2129191102","https://openalex.org/W2134383396","https://openalex.org/W2138054245","https://openalex.org/W2144412213","https://openalex.org/W2145541334","https://openalex.org/W2146894091","https://openalex.org/W2152797116","https://openalex.org/W2154410785","https://openalex.org/W2154899385","https://openalex.org/W2168833908","https://openalex.org/W2913399920","https://openalex.org/W3183393539","https://openalex.org/W4244017338","https://openalex.org/W6682607450"],"related_works":["https://openalex.org/W2955990109","https://openalex.org/W2121067345","https://openalex.org/W3209251257","https://openalex.org/W2120104138","https://openalex.org/W2160356423","https://openalex.org/W2131239515","https://openalex.org/W2246286285","https://openalex.org/W2024590010","https://openalex.org/W1894893224","https://openalex.org/W2162750207"],"abstract_inverted_index":{"The":[0,20,85],"purpose":[1],"of":[2,23,52,89],"this":[3,53],"paper":[4],"is":[5,26,93],"to":[6,28],"present":[7],"new":[8,83],"image":[9],"coding":[10,54,91],"schemes":[11,92],"based":[12],"on":[13,68],"a":[14],"predictive":[15,21],"vector":[16],"quantization":[17,44],"(PVQ)":[18],"approach.":[19],"part":[22,35],"the":[24,33,38,47,75],"encoder":[25],"used":[27],"partially":[29],"remove":[30],"redundancy,":[31],"and":[32,41,63,78],"VQ":[34],"further":[36],"removes":[37],"residual":[39],"redundancy":[40],"selects":[42],"good":[43],"levels":[45],"for":[46],"global":[48],"waveform.":[49],"Two":[50],"implementations":[51],"approach":[55],"have":[56],"been":[57],"devised,":[58],"namely,":[59],"sliding":[60],"block":[61,64],"PVQ":[62],"tree":[65,79],"PVQ.":[66],"Simulations":[67],"real":[69],"images":[70],"show":[71],"significant":[72],"improvement":[73],"over":[74],"conventional":[76],"DPCM":[77],"codes":[80],"using":[81],"these":[82,90],"techniques.":[84],"strong":[86],"robustness":[87],"property":[88],"also":[94],"experimentally":[95],"demonstrated.":[96]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}