{"id":"https://openalex.org/W1577644847","doi":"https://doi.org/10.1109/icassp.1987.1169521","title":"Sub-band coding of images using predictive vector quantization","display_name":"Sub-band coding of images using predictive vector quantization","publication_year":2005,"publication_date":"2005-03-24","ids":{"openalex":"https://openalex.org/W1577644847","doi":"https://doi.org/10.1109/icassp.1987.1169521","mag":"1577644847"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1987.1169521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1987.1169521","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","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/A5076059867","display_name":"Peter Westerink","orcid":null},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"P. Westerink","raw_affiliation_strings":["Department of Electrical Engineering, Information Theory Group, Delft University of Technnology, Delft, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Information Theory Group, Delft University of Technnology, Delft, Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078931169","display_name":"J. Biemond","orcid":"https://orcid.org/0000-0001-5300-8274"},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"J. Biemond","raw_affiliation_strings":["Department of Electrical Engineering, Information Theory Group, Delft University of Technnology, Delft, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Information Theory Group, Delft University of Technnology, Delft, Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077716820","display_name":"D.E. Boekee","orcid":null},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"D. Boekee","raw_affiliation_strings":["Department of Electrical Engineering, Information Theory Group, Delft University of Technnology, Delft, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Information Theory Group, Delft University of Technnology, Delft, Netherlands","institution_ids":["https://openalex.org/I98358874"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2991,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.57428762,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"1378","last_page":"1381"},"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":0.9991999864578247,"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/T11034","display_name":"Digital Filter Design and Implementation","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.8794430494308472},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5396513938903809},{"id":"https://openalex.org/keywords/linde\u2013buzo\u2013gray-algorithm","display_name":"Linde\u2013Buzo\u2013Gray algorithm","score":0.4828541874885559},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47055697441101074},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.466740220785141},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46358394622802734},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4607587456703186},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4521685540676117},{"id":"https://openalex.org/keywords/harmonic-vector-excitation-coding","display_name":"Harmonic Vector Excitation Coding","score":0.4404185116291046},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4222140312194824},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.3650777339935303},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32212895154953003},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.22346147894859314}],"concepts":[{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.8794430494308472},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5396513938903809},{"id":"https://openalex.org/C93372532","wikidata":"https://www.wikidata.org/wiki/Q6552455","display_name":"Linde\u2013Buzo\u2013Gray algorithm","level":3,"score":0.4828541874885559},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47055697441101074},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.466740220785141},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46358394622802734},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4607587456703186},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4521685540676117},{"id":"https://openalex.org/C80167644","wikidata":"https://www.wikidata.org/wiki/Q463990","display_name":"Harmonic Vector Excitation Coding","level":3,"score":0.4404185116291046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4222140312194824},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.3650777339935303},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32212895154953003},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.22346147894859314},{"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/icassp.1987.1169521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1987.1169521","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","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":17,"referenced_works":["https://openalex.org/W1577644847","https://openalex.org/W1584713952","https://openalex.org/W1627215994","https://openalex.org/W1690240707","https://openalex.org/W1830813422","https://openalex.org/W1915466985","https://openalex.org/W1983408778","https://openalex.org/W1985814307","https://openalex.org/W2048916503","https://openalex.org/W2134383396","https://openalex.org/W2139797453","https://openalex.org/W2142197336","https://openalex.org/W2153639720","https://openalex.org/W2165055491","https://openalex.org/W6638731828","https://openalex.org/W6680921152","https://openalex.org/W6684645939"],"related_works":["https://openalex.org/W2115984063","https://openalex.org/W2377001183","https://openalex.org/W3209251257","https://openalex.org/W2161287643","https://openalex.org/W2534663775","https://openalex.org/W1850550719","https://openalex.org/W2138799587","https://openalex.org/W2436493863","https://openalex.org/W2167107465","https://openalex.org/W2098408083"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,23,39,61,70,81,108,130],"form":[4],"of":[5,8,14,31,42,73],"sub-band":[6],"coding":[7],"images":[9,126],"in":[10,22,55,112],"which":[11],"the":[12,32,98,113],"advantages":[13],"both":[15,124],"DPCM":[16],"and":[17,48,65,84,119,128],"vector":[18,63,71,77,90,93],"quantization":[19],"are":[20,58],"combined":[21],"single":[24,82],"subband":[25],"coder.":[26],"A":[27],"16":[28,51],"band":[29,35],"decomposition":[30],"image":[33],"frequency":[34],"is":[36,78,87],"employed":[37],"using":[38,69,89],"tree":[40],"structure":[41],"two-dimensional":[43],"separable":[44],"quadrature":[45],"mirror":[46],"filters":[47],"decimators.":[49],"The":[50],"parallel":[52],"sub-bands":[53],"created":[54],"this":[56,92,105],"way":[57],"regarded":[59],"as":[60,67,80],"16-dimensional":[62],"process":[64],"coded":[66,88],"such":[68],"equivalent":[72],"DPCM.":[74],"Here":[75],"each":[76],"predicted":[79],"quantity":[83],"its":[85],"residual":[86],"quantization,":[91],"quantizer":[94],"being":[95],"nested":[96],"within":[97],"vector-DPCM":[99],"loop.":[100],"As":[101],"will":[102],"be":[103],"shown":[104],"technique":[106],"yields":[107],"good":[109],"SNR":[110],"performance":[111],"bit":[114],"rate":[115],"region":[116],"between":[117],"0.4":[118],"0.7":[120],"bits":[121],"per":[122],"pixel,":[123],"for":[125],"inside":[127],"outside":[129],"large":[131],"training":[132],"set.":[133]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
