{"id":"https://openalex.org/W2613743774","doi":"https://doi.org/10.1109/tip.2017.2783621","title":"Fast 2D Complex Gabor Filter With Kernel Decomposition","display_name":"Fast 2D Complex Gabor Filter With Kernel Decomposition","publication_year":2017,"publication_date":"2017-12-14","ids":{"openalex":"https://openalex.org/W2613743774","doi":"https://doi.org/10.1109/tip.2017.2783621","mag":"2613743774","pmid":"https://pubmed.ncbi.nlm.nih.gov/29346090"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2017.2783621","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2017.2783621","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":"https://openalex.org/A5109464360","display_name":"Jaeyoon Kim","orcid":"https://orcid.org/0000-0002-4692-8467"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaeyoon Kim","raw_affiliation_strings":["Department of Computer Science, KAIST, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, KAIST, Daejeon, South Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048491813","display_name":"Suhyuk Um","orcid":null},"institutions":[{"id":"https://openalex.org/I196345858","display_name":"Chungnam National University","ror":"https://ror.org/0227as991","country_code":"KR","type":"education","lineage":["https://openalex.org/I196345858"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Suhyuk Um","raw_affiliation_strings":["Department of Computer Science and Engineering, Chungnam National University, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Chungnam National University, Daejeon, South Korea","institution_ids":["https://openalex.org/I196345858"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037006973","display_name":"Dongbo Min","orcid":"https://orcid.org/0000-0003-4825-5240"},"institutions":[{"id":"https://openalex.org/I138925566","display_name":"Ewha Womans University","ror":"https://ror.org/053fp5c05","country_code":"KR","type":"education","lineage":["https://openalex.org/I138925566"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dongbo Min","raw_affiliation_strings":["Department of Computer Science and Engineering, Ewha Womans University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-4825-5240","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Ewha Womans University, Seoul, South Korea","institution_ids":["https://openalex.org/I138925566"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6314,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.77599294,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"27","issue":"4","first_page":"1713","last_page":"1722"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9993000030517578,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9993000030517578,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9993000030517578,"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":0.9959999918937683,"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/gabor-filter","display_name":"Gabor filter","score":0.7119549512863159},{"id":"https://openalex.org/keywords/gabor-wavelet","display_name":"Gabor wavelet","score":0.6921593546867371},{"id":"https://openalex.org/keywords/filter-bank","display_name":"Filter bank","score":0.642722487449646},{"id":"https://openalex.org/keywords/gabor-transform","display_name":"Gabor transform","score":0.6420080065727234},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.619437575340271},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5744672417640686},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5367627739906311},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5181897282600403},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5164661407470703},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.4951395094394684},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.49082955718040466},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45674341917037964},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.41029125452041626},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36918872594833374},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3276907801628113},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.3154377341270447},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.2370557188987732},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12036588788032532},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.11150413751602173},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.08299413323402405},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.0712653398513794}],"concepts":[{"id":"https://openalex.org/C2779883129","wikidata":"https://www.wikidata.org/wiki/Q2447890","display_name":"Gabor filter","level":3,"score":0.7119549512863159},{"id":"https://openalex.org/C136902061","wikidata":"https://www.wikidata.org/wiki/Q16981559","display_name":"Gabor wavelet","level":5,"score":0.6921593546867371},{"id":"https://openalex.org/C100515483","wikidata":"https://www.wikidata.org/wiki/Q3268235","display_name":"Filter bank","level":3,"score":0.642722487449646},{"id":"https://openalex.org/C173149727","wikidata":"https://www.wikidata.org/wiki/Q996397","display_name":"Gabor transform","level":4,"score":0.6420080065727234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.619437575340271},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5744672417640686},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5367627739906311},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5181897282600403},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5164661407470703},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.4951395094394684},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.49082955718040466},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45674341917037964},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.41029125452041626},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36918872594833374},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3276907801628113},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.3154377341270447},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2370557188987732},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12036588788032532},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.11150413751602173},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.08299413323402405},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.0712653398513794},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2017.2783621","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2017.2783621","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:29346090","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29346090","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/G6267577425","display_name":null,"funder_award_id":"NRF-2015R1D1A1A01061143","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W908141153","https://openalex.org/W1192631801","https://openalex.org/W1697514459","https://openalex.org/W1966770921","https://openalex.org/W1979460758","https://openalex.org/W1979743748","https://openalex.org/W1987828284","https://openalex.org/W1990131646","https://openalex.org/W1996021349","https://openalex.org/W2012197260","https://openalex.org/W2015207482","https://openalex.org/W2019904315","https://openalex.org/W2021480592","https://openalex.org/W2031802401","https://openalex.org/W2058098602","https://openalex.org/W2065924773","https://openalex.org/W2098684142","https://openalex.org/W2106873328","https://openalex.org/W2112162870","https://openalex.org/W2120954940","https://openalex.org/W2125375535","https://openalex.org/W2130982917","https://openalex.org/W2132361536","https://openalex.org/W2155919893","https://openalex.org/W2160956336","https://openalex.org/W2167034998","https://openalex.org/W2169856283","https://openalex.org/W2171574223","https://openalex.org/W2180187800","https://openalex.org/W2478628445","https://openalex.org/W2479728907","https://openalex.org/W2535531283","https://openalex.org/W4247811648"],"related_works":["https://openalex.org/W1905998934","https://openalex.org/W1560071024","https://openalex.org/W2070838085","https://openalex.org/W2382852560","https://openalex.org/W2368583888","https://openalex.org/W3156532881","https://openalex.org/W2355879620","https://openalex.org/W1830749786","https://openalex.org/W2066448268","https://openalex.org/W2373012758"],"abstract_inverted_index":{"2D":[0,27,98,169],"complex":[1,28,99],"Gabor":[2,29,46,70,100,124,146,190],"filtering":[3,34,47,60,112,208],"has":[4],"found":[5],"numerous":[6],"applications":[7],"in":[8,18,135,180,188],"the":[9,56,69,73,97,105,123,132,142,145,177,189,196,202],"fields":[10],"of":[11,33,144],"computer":[12],"vision":[13],"and":[14,39,65,84,116],"image":[15],"processing.":[16],"Especially,":[17],"some":[19],"applications,":[20],"it":[21],"is":[22],"often":[23],"needed":[24],"to":[25,81,126,182],"compute":[26],"filter":[30,71,101,147],"bank":[31,102,148],"consisting":[32],"outputs":[35],"at":[36,62,113,154],"multiple":[37,82,114],"orientations":[38,83,115],"frequencies.":[40,85,117],"Although":[41],"several":[42],"approaches":[43],"for":[44,58,168],"fast":[45,129,166],"have":[48],"been":[49],"proposed,":[50],"they":[51],"focus":[52],"primarily":[53],"on":[54],"reducing":[55,104,141],"runtime":[57,143],"performing":[59,111],"once":[61],"specific":[63,156],"orientation":[64],"frequency.":[66],"To":[67],"obtain":[68],"bank,":[72],"existing":[74],"methods":[75],"are":[76],"repeatedly":[77],"applied":[78],"with":[79,131],"respect":[80],"In":[86],"this":[87,160],"paper,":[88],"we":[89,162],"propose":[90,164],"a":[91,128,136,155,165],"novel":[92],"approach":[93,167],"that":[94,108,175,195],"efficiently":[95],"computes":[96],"by":[103,149],"computational":[106],"redundancy":[107],"arises":[109],"when":[110],"The":[118],"proposed":[119,197],"method":[120,198],"first":[121],"decomposes":[122],"kernel":[125,134,179],"allow":[127],"convolution":[130],"Gaussian":[133,178],"separable":[137],"manner.":[138],"This":[139],"enables":[140],"reusing":[150],"intermediate":[151],"results":[152,193],"computed":[153],"orientation.":[157],"By":[158],"extending":[159],"idea,":[161],"also":[163],"localized":[170],"sliding":[171],"discrete":[172],"Fourier":[173],"transform":[174],"uses":[176],"order":[181],"lend":[183],"spatial":[184],"localization":[185],"ability":[186],"as":[187],"filter.":[191],"Experimental":[192],"demonstrate":[194],"runs":[199],"faster":[200],"than":[201],"state-of-the-art":[203],"methods,":[204],"while":[205],"maintaining":[206],"similar":[207],"quality.":[209]},"counts_by_year":[{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":7},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}