乐胖代购免代理版

{"id":"https://openalex.org/W2132923618","doi":"https://doi.org/10.1109/icassp.2006.1660300","title":"Spatio-Temporal Approach for Noise Estimation","display_name":"Spatio-Temporal Approach for Noise Estimation","publication_year":2006,"publication_date":"2006-08-02","ids":{"openalex":"https://openalex.org/W2132923618","doi":"https://doi.org/10.1109/icassp.2006.1660300","mag":"2132923618"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2006.1660300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5076894523","display_name":"Vladimir Zlokolica","orcid":"https://orcid.org/0000-0002-1068-2581"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"V. Zlokolica","raw_affiliation_strings":["Dept. of Telecommun. & Inf. Process., Ghent Univ."],"affiliations":[{"raw_affiliation_string":"Dept. of Telecommun. & Inf. Process., Ghent Univ.","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031078128","display_name":"Aleksandra Pi\u017eurica","orcid":"https://orcid.org/0000-0002-9322-4999"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"A. Pizurica","raw_affiliation_strings":["Dept. of Telecommun. & Inf. Process., Ghent Univ."],"affiliations":[{"raw_affiliation_string":"Dept. of Telecommun. & Inf. Process., Ghent Univ.","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067368696","display_name":"Ewout Vansteenkiste","orcid":null},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"E. Vansteenkiste","raw_affiliation_strings":["Dept. of Telecommun. & Inf. Process., Ghent Univ."],"affiliations":[{"raw_affiliation_string":"Dept. of Telecommun. & Inf. Process., Ghent Univ.","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071483672","display_name":"Wilfried Philips","orcid":"https://orcid.org/0000-0003-4456-4353"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"W. Philips","raw_affiliation_strings":["Dept. of Telecommun. & Inf. Process., Ghent Univ."],"affiliations":[{"raw_affiliation_string":"Dept. of Telecommun. & Inf. Process., Ghent Univ.","institution_ids":["https://openalex.org/I32597200"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.245,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":2,"citation_normalized_percentile":{"value":0.310606,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":68,"max":72},"biblio":{"volume":"2","issue":null,"first_page":"II","last_page":"148"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":1.0,"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":1.0,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.999,"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/gaussian-noise","display_name":"Gaussian Noise","score":0.6575088},{"id":"https://openalex.org/keywords/value-noise","display_name":"Value noise","score":0.6030941},{"id":"https://openalex.org/keywords/gradient-noise","display_name":"Gradient noise","score":0.599503},{"id":"https://openalex.org/keywords/image-noise","display_name":"Image noise","score":0.4180998}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6814244},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.661018},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6575088},{"id":"https://openalex.org/C182163834","wikidata":"https://www.wikidata.org/wiki/Q2926529","display_name":"Value noise","level":5,"score":0.6030941},{"id":"https://openalex.org/C200378446","wikidata":"https://www.wikidata.org/wiki/Q4147391","display_name":"Gradient noise","level":5,"score":0.599503},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.54038054},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.540327},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5357517},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5203135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45472115},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42806762},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42696267},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.4180998},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19966984},{"id":"https://openalex.org/C187612029","wikidata":"https://www.wikidata.org/wiki/Q17083130","display_name":"Noise floor","level":4,"score":0.17861593},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.17406505},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.058844537}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2006.1660300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":10,"referenced_works":["https://openalex.org/W1992328824","https://openalex.org/W2115755118","https://openalex.org/W2149825794","https://openalex.org/W2166181515","https://openalex.org/W2171948434","https://openalex.org/W2480965226","https://openalex.org/W3102784098","https://openalex.org/W4214806317","https://openalex.org/W4233323564","https://openalex.org/W75297173"],"related_works":["https://openalex.org/W4297491189","https://openalex.org/W2955414824","https://openalex.org/W2545294132","https://openalex.org/W2124212511","https://openalex.org/W2016976236","https://openalex.org/W2013771251","https://openalex.org/W2005333371","https://openalex.org/W2004836404","https://openalex.org/W1969252538","https://openalex.org/W1964290457"],"abstract_inverted_index":{"We":[0],"propose":[1],"an":[2],"efficient":[3],"and":[4,26,53,109,116,128],"accurate":[5,102],"wavelet":[6,88],"based":[7,89],"noise":[8,14,38,86,106,117,126],"estimation":[9,81,107,127],"method":[10,20,99],"for":[11,56,79,92,124],"white":[12],"Gaussian":[13,85],"in":[15,29,33,49,87],"video":[16,31,90],"sequences.":[17],"The":[18,40,71],"proposed":[19,76,98],"analyzes":[21],"the":[22,30,37,45,50,57,61,75,80,83,97,122],"distribution":[23],"of":[24,74,82],"spatial":[25],"temporal":[27],"gradients":[28],"sequence":[32,64],"order":[34],"to":[35,60,112],"estimate":[36,41],"variance.":[39],"is":[42,54,78,100],"derived":[43],"from":[44],"most":[46],"frequent":[47],"gradient":[48],"two":[51],"distributions":[52],"compensated":[55],"errors":[58],"due":[59],"spatio-temporal":[62,114],"image":[63],"content,":[65],"by":[66],"a":[67],"novel":[68],"correction":[69],"function.":[70],"main":[72],"application":[73],"algorithm":[77,123],"stationary":[84],"processing,":[91],"which":[93],"we":[94,120],"show":[95],"that":[96],"more":[101],"than":[103],"other":[104],"state-of-the-art":[105],"techniques":[108],"less":[110],"sensitive":[111],"varying":[113],"content":[115],"level.":[118],"Furthermore,":[119],"adapt":[121],"local":[125],"test":[129],"its":[130],"performance.":[131]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2132923618","counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2025-01-17T06:21:37.448730","created_date":"2016-06-24"}