{"id":"https://openalex.org/W2369676483","doi":"https://doi.org/10.1109/spcom.2016.7746609","title":"Fast and high-quality bilateral filtering using Gauss-Chebyshev approximation","display_name":"Fast and high-quality bilateral filtering using Gauss-Chebyshev approximation","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2369676483","doi":"https://doi.org/10.1109/spcom.2016.7746609","mag":"2369676483"},"language":"en","primary_location":{"id":"doi:10.1109/spcom.2016.7746609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spcom.2016.7746609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Signal Processing and Communications (SPCOM)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1605.02178","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080914177","display_name":"Sanjay Ghosh","orcid":"https://orcid.org/0000-0002-0474-5072"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Sanjay Ghosh","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Science, Bangalore, India","Dept. of Electrical Engineering, Indian Institute of Science, Bangalore, INDIA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]},{"raw_affiliation_string":"Dept. of Electrical Engineering, Indian Institute of Science, Bangalore, INDIA","institution_ids":["https://openalex.org/I59270414"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045035201","display_name":"Kunal N. Chaudhury","orcid":"https://orcid.org/0000-0002-8136-605X"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kunal N. Chaudhury","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Science, Bangalore, India","Dept. of Electrical Engineering, Indian Institute of Science, Bangalore, INDIA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]},{"raw_affiliation_string":"Dept. of Electrical Engineering, Indian Institute of Science, Bangalore, INDIA","institution_ids":["https://openalex.org/I59270414"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5080914177"],"corresponding_institution_ids":["https://openalex.org/I59270414"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03081297,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9998999834060669,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9983999729156494,"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/bilateral-filter","display_name":"Bilateral filter","score":0.8586364984512329},{"id":"https://openalex.org/keywords/gaussian-filter","display_name":"Gaussian filter","score":0.7777197360992432},{"id":"https://openalex.org/keywords/gaussian-blur","display_name":"Gaussian blur","score":0.7487316131591797},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6966590881347656},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.6003901958465576},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5760967135429382},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5620713233947754},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.5614864826202393},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5372197031974792},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5301065444946289},{"id":"https://openalex.org/keywords/edge-preserving-smoothing","display_name":"Edge-preserving smoothing","score":0.5292305946350098},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.48334309458732605},{"id":"https://openalex.org/keywords/sigma","display_name":"Sigma","score":0.47128361463546753},{"id":"https://openalex.org/keywords/chebyshev-filter","display_name":"Chebyshev filter","score":0.46048128604888916},{"id":"https://openalex.org/keywords/kernel-adaptive-filter","display_name":"Kernel adaptive filter","score":0.4577331840991974},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4325113594532013},{"id":"https://openalex.org/keywords/gauss","display_name":"Gauss","score":0.4322466254234314},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41097766160964966},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40863046050071716},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.27735602855682373},{"id":"https://openalex.org/keywords/filter-design","display_name":"Filter design","score":0.25442469120025635},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2394375503063202},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0851736068725586},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.0813744068145752},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.0759463906288147}],"concepts":[{"id":"https://openalex.org/C156140930","wikidata":"https://www.wikidata.org/wiki/Q860417","display_name":"Bilateral filter","level":3,"score":0.8586364984512329},{"id":"https://openalex.org/C65892221","wikidata":"https://www.wikidata.org/wiki/Q1113935","display_name":"Gaussian filter","level":3,"score":0.7777197360992432},{"id":"https://openalex.org/C104317376","wikidata":"https://www.wikidata.org/wiki/Q1894545","display_name":"Gaussian blur","level":5,"score":0.7487316131591797},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6966590881347656},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.6003901958465576},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5760967135429382},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5620713233947754},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.5614864826202393},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5372197031974792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5301065444946289},{"id":"https://openalex.org/C141651230","wikidata":"https://www.wikidata.org/wiki/Q5337637","display_name":"Edge-preserving smoothing","level":4,"score":0.5292305946350098},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.48334309458732605},{"id":"https://openalex.org/C2778049214","wikidata":"https://www.wikidata.org/wiki/Q7512234","display_name":"Sigma","level":2,"score":0.47128361463546753},{"id":"https://openalex.org/C21424316","wikidata":"https://www.wikidata.org/wiki/Q718621","display_name":"Chebyshev filter","level":2,"score":0.46048128604888916},{"id":"https://openalex.org/C13107197","wikidata":"https://www.wikidata.org/wiki/Q6394192","display_name":"Kernel adaptive filter","level":4,"score":0.4577331840991974},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4325113594532013},{"id":"https://openalex.org/C161794534","wikidata":"https://www.wikidata.org/wiki/Q177493","display_name":"Gauss","level":2,"score":0.4322466254234314},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41097766160964966},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40863046050071716},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27735602855682373},{"id":"https://openalex.org/C22597639","wikidata":"https://www.wikidata.org/wiki/Q5449227","display_name":"Filter design","level":3,"score":0.25442469120025635},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2394375503063202},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0851736068725586},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0813744068145752},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.0759463906288147},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/spcom.2016.7746609","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spcom.2016.7746609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Signal Processing and Communications (SPCOM)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.iisc.ac.in:56148","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196309","display_name":"NOT FOUND REPOSITORY (Indian Institute of Science Bangalore)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59270414","host_organization_name":"Indian Institute of Science Bangalore","host_organization_lineage":["https://openalex.org/I59270414"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceedings"},{"id":"pmh:oai:arXiv.org:1605.02178","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1605.02178","pdf_url":"https://arxiv.org/pdf/1605.02178","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2369676483","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1605.02178","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1605.02178","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1605.02178","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1605.02178","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1605.02178","pdf_url":"https://arxiv.org/pdf/1605.02178","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W2369676483.pdf"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W1492046297","https://openalex.org/W1528144695","https://openalex.org/W1995194116","https://openalex.org/W2019491495","https://openalex.org/W2075832873","https://openalex.org/W2099244020","https://openalex.org/W2106884232","https://openalex.org/W2107462260","https://openalex.org/W2123782500","https://openalex.org/W2144531167","https://openalex.org/W2162618331","https://openalex.org/W2796837256","https://openalex.org/W2912690953","https://openalex.org/W6681426593","https://openalex.org/W7070871703"],"related_works":["https://openalex.org/W3123505101","https://openalex.org/W2107462260","https://openalex.org/W2891878684","https://openalex.org/W2088352866","https://openalex.org/W2126814866","https://openalex.org/W3015721417","https://openalex.org/W2295549597","https://openalex.org/W2970037012","https://openalex.org/W2889777035","https://openalex.org/W2858196343","https://openalex.org/W1601889892","https://openalex.org/W1964772475","https://openalex.org/W1971926318","https://openalex.org/W2829607438","https://openalex.org/W1987844198","https://openalex.org/W2022325331","https://openalex.org/W1979369422","https://openalex.org/W2768741585","https://openalex.org/W1983389993","https://openalex.org/W2891251149"],"abstract_inverted_index":{"The":[0,21],"bilateral":[1,43,57,104],"filter":[2,22,44,58],"is":[3,76,87,93,134,150,167],"an":[4,99],"edge-preserving":[5,34],"smoother":[6],"that":[7,89,133,146,164],"has":[8],"diverse":[9],"applications":[10],"in":[11,95,154,173],"image":[12],"processing,":[13],"computer":[14,16],"vision,":[15],"graphics,":[17],"and":[18,127,177],"computational":[19],"photography.":[20],"uses":[23],"a":[24,29],"spatial":[25,82],"kernel":[26,31],"along":[27],"with":[28,169],"range":[30],"to":[32,115,157],"perform":[33],"smoothing.":[35],"In":[36,84],"this":[37],"paper,":[38],"we":[39,107],"consider":[40],"the":[41,47,55,77,81,90,102,111,138,141,147,158,165],"Gaussian":[42,56,103],"where":[45,71],"both":[46],"kernels":[48],"are":[49],"Gaussian.":[50,83],"A":[51],"direct":[52,91,159],"implementation":[53,92],"of":[54,80,101,113,140,175],"requires":[59],"O(\u03c3":[60],"<sub":[61,73,123],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[62,65,74,124],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">s</sub>":[63,75,125],"<sup":[64],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[66],")":[67],"operations":[68,114],"per":[69,117],"pixel,":[70],"\u03c3":[72,122],"standard":[78],"deviation":[79],"fact,":[85],"it":[86],"well-known":[88],"slow":[94],"practice.":[96],"We":[97,144,161],"present":[98],"approximation":[100,149,166],"filter,":[105],"whereby":[106],"can":[108],"cut":[109],"down":[110],"number":[112],"O(1)":[116],"pixel":[118],"for":[119],"any":[120],"arbitrary":[121],",":[126],"yet":[128],"achieve":[129],"very":[130],"high-quality":[131],"filtering":[132],"almost":[135],"indistinguishable":[136],"from":[137],"output":[139],"original":[142],"filter.":[143],"demonstrate":[145,163],"proposed":[148],"few":[151],"orders":[152],"faster":[153],"practice":[155],"compared":[156],"implementation.":[160],"also":[162],"competitive":[168],"existing":[170],"fast":[171],"algorithms":[172],"terms":[174],"speed":[176],"accuracy.":[178]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}