{"id":"https://openalex.org/W1972350229","doi":"https://doi.org/10.1109/jsac.1987.1146625","title":"Recursive Temporal Filtering and Frame Rate Reduction for Image Coding","display_name":"Recursive Temporal Filtering and Frame Rate Reduction for Image Coding","publication_year":1987,"publication_date":"1987-08-01","ids":{"openalex":"https://openalex.org/W1972350229","doi":"https://doi.org/10.1109/jsac.1987.1146625","mag":"1972350229"},"language":"en","primary_location":{"id":"doi:10.1109/jsac.1987.1146625","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsac.1987.1146625","pdf_url":null,"source":{"id":"https://openalex.org/S90422530","display_name":"IEEE Journal on Selected Areas in Communications","issn_l":"0733-8716","issn":["0733-8716","1558-0008"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Journal on Selected Areas in 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/A5111579326","display_name":"Wen-Hsiung Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wen-Hsiung Chen","raw_affiliation_strings":["Compression Laboratories, Inc., San Jose, CA, USA","Compression Labs, Inc., San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Compression Laboratories, Inc., San Jose, CA, USA","institution_ids":[]},{"raw_affiliation_string":"Compression Labs, Inc., San Jose, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014464462","display_name":"D. N. Hein","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"D. Hein","raw_affiliation_strings":["Compression Laboratories, Inc., San Jose, CA, USA","[Compression Laboratories, Inc., San Jose, CA, USA]"],"affiliations":[{"raw_affiliation_string":"Compression Laboratories, Inc., San Jose, CA, USA","institution_ids":[]},{"raw_affiliation_string":"[Compression Laboratories, Inc., San Jose, CA, USA]","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5111579326"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6318,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.70018093,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":"7","first_page":"1155","last_page":"1165"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9997000098228455,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9997000098228455,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9997000098228455,"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":0.9995999932289124,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/inter-frame","display_name":"Inter frame","score":0.7756909132003784},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6585129499435425},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5584475994110107},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5350657105445862},{"id":"https://openalex.org/keywords/intra-frame","display_name":"Intra-frame","score":0.5057454109191895},{"id":"https://openalex.org/keywords/residual-frame","display_name":"Residual frame","score":0.47117879986763},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4496609568595886},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4424198269844055},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4336734414100647},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4076387286186218},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3874187171459198},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.36694368720054626},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33743226528167725},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3243555724620819},{"id":"https://openalex.org/keywords/reference-frame","display_name":"Reference frame","score":0.28745731711387634},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2674836814403534},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10925918817520142}],"concepts":[{"id":"https://openalex.org/C39394851","wikidata":"https://www.wikidata.org/wiki/Q921594","display_name":"Inter frame","level":4,"score":0.7756909132003784},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6585129499435425},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5584475994110107},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5350657105445862},{"id":"https://openalex.org/C125864890","wikidata":"https://www.wikidata.org/wiki/Q1262687","display_name":"Intra-frame","level":3,"score":0.5057454109191895},{"id":"https://openalex.org/C204641915","wikidata":"https://www.wikidata.org/wiki/Q7315509","display_name":"Residual frame","level":4,"score":0.47117879986763},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4496609568595886},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4424198269844055},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4336734414100647},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4076387286186218},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3874187171459198},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.36694368720054626},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33743226528167725},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3243555724620819},{"id":"https://openalex.org/C172849965","wikidata":"https://www.wikidata.org/wiki/Q3148875","display_name":"Reference frame","level":3,"score":0.28745731711387634},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2674836814403534},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10925918817520142},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jsac.1987.1146625","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsac.1987.1146625","pdf_url":null,"source":{"id":"https://openalex.org/S90422530","display_name":"IEEE Journal on Selected Areas in Communications","issn_l":"0733-8716","issn":["0733-8716","1558-0008"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Journal on Selected Areas in 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":5,"referenced_works":["https://openalex.org/W1983119563","https://openalex.org/W1985673600","https://openalex.org/W2005245503","https://openalex.org/W2015491854","https://openalex.org/W2113504184"],"related_works":["https://openalex.org/W2149600693","https://openalex.org/W1965479822","https://openalex.org/W2004879996","https://openalex.org/W2099372942","https://openalex.org/W2124866860","https://openalex.org/W2008346734","https://openalex.org/W3012474759","https://openalex.org/W1857694849","https://openalex.org/W2033053619","https://openalex.org/W1758919547"],"abstract_inverted_index":{"The":[0,53,76],"effect":[1,30,77],"of":[2,13,31,40,55,78,111,128,134,143],"temporal":[3,26,79],"recursive":[4],"filtering":[5,32,44,80,126,151],"and":[6,33,46,81,101],"frame":[7,34,82,109,132],"rate":[8,35,83,88,110,121,133],"reduction":[9,36,84,118,141],"on":[10,37],"a":[11,19,65,98,108,116,125,131],"sequence":[12,68,96],"moving":[14],"images":[15,154],"is":[16,58,89,122,146],"investigated.":[17],"Following":[18],"well-known":[20],"first-order":[21,73],"Markov":[22,74],"model":[23],"for":[24],"the":[25,29,38,61,72,86,93,149,159],"domain":[27],"data,":[28],"values":[39],"variance,":[41],"correlation":[42],"coefficient,":[43],"distortion,":[45],"interframe":[47,100],"prediction":[48],"error":[49],"are":[50,155],"mathematically":[51],"derived.":[52],"validity":[54],"these":[56],"derivations":[57],"verified":[59],"by":[60,91],"experimental":[62],"results":[63],"using":[64,97,148],"CCITT":[66,94],"standard":[67,95],"which":[69],"closely":[70],"follows":[71],"model.":[75],"to":[85,157],"coding":[87,120],"examined":[90],"encoding":[92],"combined":[99],"intraframe":[102],"Scene":[103],"Adaptive":[104],"Coding":[105],"system.":[106],"At":[107,130],"30":[112],"frames":[113,136],"per":[114,137],"second,":[115,138],"2:1":[117],"in":[119],"obtained":[123,147],"with":[124],"coefficient":[127],"0.5.":[129],"10":[135],"an":[139],"additional":[140],"factor":[142],"nearly":[144],"2":[145],"same":[150],"coefficient.":[152],"Selected":[153],"presented":[156],"demonstrate":[158],"subjective":[160],"effect.":[161]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
