{"id":"https://openalex.org/W2027282286","doi":"https://doi.org/10.1109/vcip.2011.6115991","title":"Prediction of DCT coefficients considering motion compensation error distributions","display_name":"Prediction of DCT coefficients considering motion compensation error distributions","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2027282286","doi":"https://doi.org/10.1109/vcip.2011.6115991","mag":"2027282286"},"language":"en","primary_location":{"id":"doi:10.1109/vcip.2011.6115991","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2011.6115991","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 Visual Communications and Image Processing (VCIP)","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/A5073058819","display_name":"Julia Schmidt","orcid":"https://orcid.org/0009-0005-6832-521X"},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Julia Schmidt","raw_affiliation_strings":["Gottfried Wilhelm Leibniz, Universitaet Hannover, Hanover, Germany","Gottfried Wilhelm Leibniz Universitaet Hannover, Germany"],"affiliations":[{"raw_affiliation_string":"Gottfried Wilhelm Leibniz, Universitaet Hannover, Hanover, Germany","institution_ids":["https://openalex.org/I114112103"]},{"raw_affiliation_string":"Gottfried Wilhelm Leibniz Universitaet Hannover, Germany","institution_ids":["https://openalex.org/I114112103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022331149","display_name":"Bernd Edler","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123192","display_name":"International Audio Laboratories Erlangen","ror":"https://ror.org/02mkz3e80","country_code":"DE","type":"facility","lineage":["https://openalex.org/I181369854","https://openalex.org/I4210123192","https://openalex.org/I4210124274","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernd Edler","raw_affiliation_strings":["International Audio Laboratories, Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"International Audio Laboratories, Erlangen, Germany","institution_ids":["https://openalex.org/I4210123192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112053510","display_name":"J\u00f6ern Ostermann","orcid":null},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Joern Ostermann","raw_affiliation_strings":["Gottfried Wilhelm Leibniz, Universitaet Hannover, Hanover, Germany","Gottfried Wilhelm Leibniz Universitaet Hannover, Germany"],"affiliations":[{"raw_affiliation_string":"Gottfried Wilhelm Leibniz, Universitaet Hannover, Hanover, Germany","institution_ids":["https://openalex.org/I114112103"]},{"raw_affiliation_string":"Gottfried Wilhelm Leibniz Universitaet Hannover, Germany","institution_ids":["https://openalex.org/I114112103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5073058819"],"corresponding_institution_ids":["https://openalex.org/I114112103"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09545188,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10741","display_name":"Video Coding and Compression Technologies","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10741","display_name":"Video Coding and Compression Technologies","score":1.0,"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"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9987999796867371,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9987000226974487,"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/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.9200423955917358},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7029250860214233},{"id":"https://openalex.org/keywords/lapped-transform","display_name":"Lapped transform","score":0.6359838247299194},{"id":"https://openalex.org/keywords/motion-compensation","display_name":"Motion compensation","score":0.5706234574317932},{"id":"https://openalex.org/keywords/transform-coding","display_name":"Transform coding","score":0.5551323890686035},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5490165948867798},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5443629026412964},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5233625173568726},{"id":"https://openalex.org/keywords/mean-squared-prediction-error","display_name":"Mean squared prediction error","score":0.5071706771850586},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.4621622562408447},{"id":"https://openalex.org/keywords/algorithmic-efficiency","display_name":"Algorithmic efficiency","score":0.4600922465324402},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42829015851020813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32523250579833984},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2508154809474945},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07866567373275757}],"concepts":[{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.9200423955917358},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7029250860214233},{"id":"https://openalex.org/C91458471","wikidata":"https://www.wikidata.org/wiki/Q17096468","display_name":"Lapped transform","level":5,"score":0.6359838247299194},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.5706234574317932},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.5551323890686035},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5490165948867798},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5443629026412964},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5233625173568726},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.5071706771850586},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.4621622562408447},{"id":"https://openalex.org/C116709606","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Algorithmic efficiency","level":3,"score":0.4600922465324402},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42829015851020813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32523250579833984},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2508154809474945},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07866567373275757}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/vcip.2011.6115991","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2011.6115991","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.295.8551","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.295.8551","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1546274697","https://openalex.org/W1594615639","https://openalex.org/W2074665009","https://openalex.org/W2086909814","https://openalex.org/W2106219841","https://openalex.org/W2140199336"],"related_works":["https://openalex.org/W3142097109","https://openalex.org/W2138702206","https://openalex.org/W2151738694","https://openalex.org/W3140834049","https://openalex.org/W2978563117","https://openalex.org/W2169808749","https://openalex.org/W1908108260","https://openalex.org/W2589122841","https://openalex.org/W2890730752","https://openalex.org/W2599701415"],"abstract_inverted_index":{"Current":[0],"video":[1],"coding":[2,57],"techniques":[3],"use":[4],"a":[5,36,43,63],"Discrete":[6],"Cosine":[7],"Transform":[8],"(DCT)":[9],"to":[10,38,55,62,72],"reduce":[11],"spatial":[12],"correlations":[13],"within":[14],"the":[15,20,27,48,51,73],"motion":[16],"estimation":[17],"residual.":[18],"Often":[19],"correlation":[21],"cannot":[22],"be":[23],"completely":[24],"eliminated":[25],"leaving":[26],"transform":[28],"coefficients":[29,41],"statistically":[30],"dependent.":[31],"The":[32],"presented":[33],"paper":[34],"proposes":[35],"method":[37],"predict":[39],"these":[40],"on":[42],"block":[44],"level":[45],"by":[46,68],"using":[47],"distribution":[49],"of":[50],"prediction":[52],"error":[53],"variance":[54],"improve":[56],"efficiency.":[58],"First":[59],"experiments":[60],"lead":[61],"reduction":[64],"in":[65],"bit":[66],"rate":[67],"1.83%":[69],"when":[70],"compared":[71],"standard":[74],"JM":[75],"17.2":[76],"implementation":[77],"results.":[78]},"counts_by_year":[],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}