{"id":"https://openalex.org/W1543051281","doi":"https://doi.org/10.1109/pcs.2015.7170087","title":"Content removal via both thresholding averaging and two dimensional discrete fractional Fourier transform","display_name":"Content removal via both thresholding averaging and two dimensional discrete fractional Fourier transform","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1543051281","doi":"https://doi.org/10.1109/pcs.2015.7170087","mag":"1543051281"},"language":"en","primary_location":{"id":"doi:10.1109/pcs.2015.7170087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs.2015.7170087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Picture Coding Symposium (PCS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5022036826","display_name":"Bingo Wing\u2010Kuen Ling","orcid":"https://orcid.org/0000-0002-0633-7224"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingo Wing-Kuen Ling","raw_affiliation_strings":["School of Info. Eng., G.D.U.T., Guangzhou, 510006, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Info. Eng., G.D.U.T., Guangzhou, 510006, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106698816","display_name":"Yaru Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaru Wang","raw_affiliation_strings":["School of Info. Eng., G.D.U.T., Guangzhou, 510006, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Info. Eng., G.D.U.T., Guangzhou, 510006, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064465418","display_name":"Zhijing Yang","orcid":"https://orcid.org/0000-0001-8336-5109"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijing Yang","raw_affiliation_strings":["School of Info. Eng., G.D.U.T., Guangzhou, 510006, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Info. Eng., G.D.U.T., Guangzhou, 510006, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020870102","display_name":"Nain Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nain Cai","raw_affiliation_strings":["School of Info. Eng., G.D.U.T., Guangzhou, 510006, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Info. Eng., G.D.U.T., Guangzhou, 510006, China","institution_ids":["https://openalex.org/I37987034"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03210615,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"262","last_page":"266"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","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"}},"topics":[{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","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"}},{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9790999889373779,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9728999733924866,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/non-uniform-discrete-fourier-transform","display_name":"Non-uniform discrete Fourier transform","score":0.689003050327301},{"id":"https://openalex.org/keywords/discrete-fourier-transform","display_name":"Discrete Fourier transform (general)","score":0.6764909029006958},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5676136016845703},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.5464339852333069},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5290670990943909},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5135695934295654},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5115123987197876},{"id":"https://openalex.org/keywords/discrete-time-fourier-transform","display_name":"Discrete-time Fourier transform","score":0.49378761649131775},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47589409351348877},{"id":"https://openalex.org/keywords/fast-fourier-transform","display_name":"Fast Fourier transform","score":0.47223588824272156},{"id":"https://openalex.org/keywords/dft-matrix","display_name":"DFT matrix","score":0.4398620128631592},{"id":"https://openalex.org/keywords/fractional-fourier-transform","display_name":"Fractional Fourier transform","score":0.4202287197113037},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.4183938205242157},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.4115736484527588},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.29472121596336365},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.25555843114852905},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.25022563338279724},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.21186953783035278},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1419242024421692},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13692286610603333},{"id":"https://openalex.org/keywords/square-matrix","display_name":"Square matrix","score":0.11439746618270874}],"concepts":[{"id":"https://openalex.org/C62058723","wikidata":"https://www.wikidata.org/wiki/Q7049066","display_name":"Non-uniform discrete Fourier transform","level":5,"score":0.689003050327301},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.6764909029006958},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5676136016845703},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.5464339852333069},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5290670990943909},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5135695934295654},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5115123987197876},{"id":"https://openalex.org/C122444316","wikidata":"https://www.wikidata.org/wiki/Q1440048","display_name":"Discrete-time Fourier transform","level":5,"score":0.49378761649131775},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47589409351348877},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.47223588824272156},{"id":"https://openalex.org/C103945485","wikidata":"https://www.wikidata.org/wiki/Q5204933","display_name":"DFT matrix","level":5,"score":0.4398620128631592},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.4202287197113037},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4183938205242157},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.4115736484527588},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.29472121596336365},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.25555843114852905},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.25022563338279724},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.21186953783035278},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1419242024421692},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13692286610603333},{"id":"https://openalex.org/C69044650","wikidata":"https://www.wikidata.org/wiki/Q2739329","display_name":"Square matrix","level":4,"score":0.11439746618270874},{"id":"https://openalex.org/C54848796","wikidata":"https://www.wikidata.org/wiki/Q339011","display_name":"Symmetric matrix","level":3,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pcs.2015.7170087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pcs.2015.7170087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Picture Coding Symposium (PCS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1970994204","https://openalex.org/W2048265462","https://openalex.org/W2052007184","https://openalex.org/W2063731679","https://openalex.org/W2086666872","https://openalex.org/W2128260023","https://openalex.org/W2129240197","https://openalex.org/W2166218655"],"related_works":["https://openalex.org/W2118155316","https://openalex.org/W3141389362","https://openalex.org/W2382218334","https://openalex.org/W2154898175","https://openalex.org/W2116983948","https://openalex.org/W2945379152","https://openalex.org/W2777066715","https://openalex.org/W2090697566","https://openalex.org/W2963406743","https://openalex.org/W1909720304"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,130,180],"novel":[4],"content":[5],"removal":[6],"technique":[7],"for":[8,110,179],"enhancing":[9],"the":[10,21,46,57,71,75,81,87,103,111,115,119,135,142,147,150,154,163,172,176],"camera":[11],"identification":[12],"performance.":[13],"Here,":[14],"very":[15],"low":[16],"bit":[17],"rate":[18],"videos":[19,151],"with":[20,39],"overall":[22,47],"noise":[23,48],"patterns":[24],"having":[25],"time":[26],"varying":[27],"statistics":[28],"are":[29,43,77,127,138,166],"considered.":[30],"First,":[31],"different":[32,40],"two":[33,89],"dimensional":[34,90],"discrete":[35,92],"fractional":[36,93],"Fourier":[37,94],"transforms":[38,76],"rotational":[41,72,143,184],"angles":[42,73,144],"applied":[44,97],"to":[45,68,80,98,153],"pattern":[49],"of":[50,53,59,62,74,84,118,149,183],"each":[51,54,60,63,99,122],"frame":[52],"video.":[55],"Second,":[56],"modulus":[58],"element":[61],"transformed":[64],"matrix":[65,101,126],"is":[66,96,107,169],"normalized":[67,100,123],"one":[69],"if":[70],"not":[78],"equal":[79],"integer":[82],"multiples":[83],"\u03c0.":[85],"Third,":[86],"corresponding":[88,104,152],"inverse":[91],"transform":[95],"and":[102,145],"real":[105,124],"part":[106],"taken":[108],"out":[109],"further":[112],"processing.":[113],"Fourth,":[114],"absolute":[116],"values":[117],"elements":[120],"in":[121],"valued":[125],"bounded":[128],"by":[129],"certain":[131],"threshold":[132],"value.":[133],"Finally,":[134],"processed":[136],"matrices":[137],"averaged":[139],"over":[140],"all":[141,146],"frames":[148],"same":[155],"camera.":[156],"Extensive":[157],"computer":[158],"numerical":[159],"simulation":[160],"results":[161],"on":[162],"correlation":[164],"performances":[165],"presented.":[167],"It":[168],"found":[170],"that":[171],"proposed":[173],"method":[174,178],"outperforms":[175],"existing":[177],"wide":[181],"range":[182],"angles.":[185]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
