{"id":"https://openalex.org/W4403758811","doi":"https://doi.org/10.1109/tip.2024.3484173","title":"<i>\u03bb</i>-Domain Rate Control via Wavelet-Based Residual Neural Network for VVC HDR Intra Coding","display_name":"<i>\u03bb</i>-Domain Rate Control via Wavelet-Based Residual Neural Network for VVC HDR Intra Coding","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4403758811","doi":"https://doi.org/10.1109/tip.2024.3484173","pmid":"https://pubmed.ncbi.nlm.nih.gov/39453801"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2024.3484173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2024.3484173","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Feng Yuan","orcid":"https://orcid.org/0009-0008-0057-5839"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Yuan","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0008-0057-5839","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081490093","display_name":"Jianjun Lei","orcid":"https://orcid.org/0000-0003-3171-7680"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianjun Lei","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-3171-7680","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058087031","display_name":"Zhaoqing Pan","orcid":"https://orcid.org/0000-0003-1390-399X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoqing Pan","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-1390-399X","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061202217","display_name":"Bo Peng","orcid":"https://orcid.org/0000-0002-6616-453X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Peng","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-6616-453X","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013151488","display_name":"Haoran Xie","orcid":"https://orcid.org/0000-0003-0965-3617"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haoran Xie","raw_affiliation_strings":["School of Data Science, Lingnan University, Hong Kong, China","Department of Computing and Decision Sciences, Lingnan University, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0003-0965-3617","affiliations":[{"raw_affiliation_string":"School of Data Science, Lingnan University, Hong Kong, China","institution_ids":[]},{"raw_affiliation_string":"Department of Computing and Decision Sciences, Lingnan University, Hong Kong, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8654,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.73864099,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"33","issue":null,"first_page":"6189","last_page":"6203"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11444","display_name":"Electromagnetic Compatibility and Noise Suppression","score":0.986299991607666,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11444","display_name":"Electromagnetic Compatibility and Noise Suppression","score":0.986299991607666,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10511","display_name":"High voltage insulation and dielectric phenomena","score":0.9800999760627747,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10468","display_name":"Photovoltaic System Optimization Techniques","score":0.9729999899864197,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6846086382865906},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6349682807922363},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6099918484687805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5519126653671265},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5386607050895691},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.49618345499038696},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.45913368463516235},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44621968269348145},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4200119376182556},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31011852622032166},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2203230857849121},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07348859310150146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6846086382865906},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6349682807922363},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6099918484687805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5519126653671265},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5386607050895691},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.49618345499038696},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.45913368463516235},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44621968269348145},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4200119376182556},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31011852622032166},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2203230857849121},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07348859310150146},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2024.3484173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2024.3484173","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:39453801","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39453801","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G826549716","display_name":null,"funder_award_id":"62322116","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W2095709228","https://openalex.org/W2106219841","https://openalex.org/W2123729354","https://openalex.org/W2146395539","https://openalex.org/W2169161136","https://openalex.org/W2194775991","https://openalex.org/W2314317712","https://openalex.org/W2407574721","https://openalex.org/W2540658878","https://openalex.org/W2552478658","https://openalex.org/W2597893405","https://openalex.org/W2736611505","https://openalex.org/W2746556728","https://openalex.org/W2766497195","https://openalex.org/W2790203435","https://openalex.org/W2791180045","https://openalex.org/W2793249124","https://openalex.org/W2793361125","https://openalex.org/W2795049052","https://openalex.org/W2801519264","https://openalex.org/W2890000486","https://openalex.org/W2936017994","https://openalex.org/W2978621718","https://openalex.org/W2995667229","https://openalex.org/W3012364666","https://openalex.org/W3013576271","https://openalex.org/W3021895009","https://openalex.org/W3022594171","https://openalex.org/W3043823510","https://openalex.org/W3113727486","https://openalex.org/W3113892883","https://openalex.org/W3127430257","https://openalex.org/W3127867299","https://openalex.org/W3152624359","https://openalex.org/W3202918664","https://openalex.org/W3205509932","https://openalex.org/W3211260255","https://openalex.org/W3212741874","https://openalex.org/W4210361933","https://openalex.org/W4210800005","https://openalex.org/W4213425175","https://openalex.org/W4312402301","https://openalex.org/W4313485590","https://openalex.org/W4320000919","https://openalex.org/W4360994344","https://openalex.org/W4380876029","https://openalex.org/W4389474378"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W2382174632","https://openalex.org/W2788972299","https://openalex.org/W2498789492","https://openalex.org/W2521347458","https://openalex.org/W2129959498","https://openalex.org/W2784060934","https://openalex.org/W2902714807","https://openalex.org/W2537489131"],"abstract_inverted_index":{"High":[0],"dynamic":[1,13],"range":[2,14],"(HDR)":[3],"video":[4,40,50,54],"offers":[5],"a":[6,77,105,141,164],"more":[7],"realistic":[8],"visual":[9],"experience":[10],"than":[11,201],"standard":[12],"(SDR)":[15],"video,":[16],"while":[17],"introducing":[18],"new":[19],"challenges":[20],"to":[21,32,59,112,131,149],"both":[22],"compression":[23],"and":[24,36,62,104,121],"transmission.":[25],"Rate":[26],"control":[27,45,82,195],"is":[28,57,84,110,147,168],"an":[29],"effective":[30],"technology":[31],"overcome":[33],"these":[34],"challenges,":[35],"ensure":[37],"optimal":[38],"HDR":[39,71,88,99,127,166,181,191],"delivery.":[41],"However,":[42],"the":[43,48,95,115,118,122,136,152,155,175,202],"rate":[44,81,119,194],"algorithm":[46,83,196],"in":[47,91,180],"latest":[49],"coding":[51,55,67,96,101,137,199],"standard,":[52],"versatile":[53],"(VVC),":[56],"tailored":[58],"SDR":[60],"videos,":[61],"does":[63],"not":[64],"produce":[65],"well":[66],"results":[68,186,200],"when":[69],"encoding":[70],"videos.":[72],"To":[73],"address":[74],"this":[75,92,209],"problem,":[76],"data-driven":[78],"\u03bb":[79,108,125,158],"-domain":[80],"proposed":[85,111,190],"for":[86,126,160,170],"VVC":[87],"intra":[89,100,128,182,192],"frames":[90],"paper.":[93],"First,":[94],"characteristics":[97],"of":[98,154,177,208],"are":[102],"analyzed,":[103],"piecewise":[106,156],"R-":[107,157],"model":[109,159],"accurately":[113,150],"determine":[114],"correlation":[116],"between":[117],"(R)":[120],"Lagrange":[123],"parameter":[124],"frames.":[129],"Then,":[130],"optimize":[132],"bit":[133],"allocation":[134],"at":[135,214],"tree":[138],"unit":[139],"(CTU)-level,":[140],"wavelet-based":[142],"residual":[143],"neural":[144],"network":[145],"(WRNN)":[146],"developed":[148],"predict":[151],"parameters":[153],"each":[161],"CTU.":[162],"Third,":[163],"large-scale":[165],"dataset":[167],"established":[169],"training":[171],"WRNN,":[172],"which":[173],"facilitates":[174],"applications":[176],"deep":[178],"learning":[179],"coding.":[183],"Extensive":[184],"experimental":[185],"show":[187],"that":[188],"our":[189],"frame":[193],"achieves":[197],"superior":[198],"state-of-the-art":[203],"algorithms.":[204],"The":[205],"source":[206],"code":[207],"work":[210],"will":[211],"be":[212],"released":[213],"https://github.com/TJU-Videocoding/WRNN.git.":[215]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
