{"id":"https://openalex.org/W2784267955","doi":"https://doi.org/10.1109/uemcon.2017.8249109","title":"Total variation denoising method to improve the detection process in IR images","display_name":"Total variation denoising method to improve the detection process in IR images","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2784267955","doi":"https://doi.org/10.1109/uemcon.2017.8249109","mag":"2784267955"},"language":"en","primary_location":{"id":"doi:10.1109/uemcon.2017.8249109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/uemcon.2017.8249109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","raw_type":"proceedings-article"},"type":"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/A5088039090","display_name":"Lina Chato","orcid":"https://orcid.org/0000-0002-5635-9472"},"institutions":[{"id":"https://openalex.org/I133999245","display_name":"University of Nevada, Las Vegas","ror":"https://ror.org/0406gha72","country_code":"US","type":"education","lineage":["https://openalex.org/I133999245"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lina Chato","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Nevada, Las Vegas (UNLV), Las Vegas, Nevada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Nevada, Las Vegas (UNLV), Las Vegas, Nevada","institution_ids":["https://openalex.org/I133999245"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112598261","display_name":"Shahram Latifi","orcid":"https://orcid.org/0000-0001-6868-5008"},"institutions":[{"id":"https://openalex.org/I133999245","display_name":"University of Nevada, Las Vegas","ror":"https://ror.org/0406gha72","country_code":"US","type":"education","lineage":["https://openalex.org/I133999245"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shahram Latifi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Nevada, Las Vegas (UNLV), Las Vegas, Nevada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Nevada, Las Vegas (UNLV), Las Vegas, Nevada","institution_ids":["https://openalex.org/I133999245"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071383424","display_name":"Pushkin Kachroo","orcid":"https://orcid.org/0000-0002-7701-8925"},"institutions":[{"id":"https://openalex.org/I133999245","display_name":"University of Nevada, Las Vegas","ror":"https://ror.org/0406gha72","country_code":"US","type":"education","lineage":["https://openalex.org/I133999245"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pushkin Kachroo","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Nevada, Las Vegas (UNLV), Las Vegas, Nevada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Nevada, Las Vegas (UNLV), Las Vegas, Nevada","institution_ids":["https://openalex.org/I133999245"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5088039090"],"corresponding_institution_ids":["https://openalex.org/I133999245"],"apc_list":null,"apc_paid":null,"fwci":0.3641,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.70338835,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"441","last_page":"447"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991000294685364,"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":0.9991000294685364,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9965000152587891,"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"}},{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.991599977016449,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/noise-reduction","display_name":"Noise reduction","score":0.7922862768173218},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7501028776168823},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.670284628868103},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6029961705207825},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5918003916740417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5887817740440369},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5854529738426208},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5735228061676025},{"id":"https://openalex.org/keywords/video-denoising","display_name":"Video denoising","score":0.5648018717765808},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5607985854148865},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.4582885801792145},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3255295753479004},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.12080490589141846},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.10770678520202637},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06137895584106445}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.7922862768173218},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7501028776168823},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.670284628868103},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6029961705207825},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5918003916740417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5887817740440369},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5854529738426208},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5735228061676025},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.5648018717765808},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5607985854148865},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.4582885801792145},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3255295753479004},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.12080490589141846},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.10770678520202637},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06137895584106445},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.0},{"id":"https://openalex.org/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/uemcon.2017.8249109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/uemcon.2017.8249109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","score":0.6299999952316284,"display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W33189562","https://openalex.org/W1545641654","https://openalex.org/W1952467837","https://openalex.org/W1963845456","https://openalex.org/W1966076396","https://openalex.org/W2000594266","https://openalex.org/W2012807998","https://openalex.org/W2019766749","https://openalex.org/W2033725016","https://openalex.org/W2037981501","https://openalex.org/W2097290407","https://openalex.org/W2103413619","https://openalex.org/W2103559027","https://openalex.org/W2122192562","https://openalex.org/W2122756437","https://openalex.org/W2129893153","https://openalex.org/W2135095945","https://openalex.org/W2163808566","https://openalex.org/W2499423397","https://openalex.org/W2507538975","https://openalex.org/W2552294130","https://openalex.org/W2558181346","https://openalex.org/W2607156215","https://openalex.org/W6730225244"],"related_works":["https://openalex.org/W2792867467","https://openalex.org/W4287081060","https://openalex.org/W2791234060","https://openalex.org/W1538114257","https://openalex.org/W2541197080","https://openalex.org/W2895947835","https://openalex.org/W1974034585","https://openalex.org/W2810018092","https://openalex.org/W2098237619","https://openalex.org/W2035842925"],"abstract_inverted_index":{"Noise":[0,62],"reduces":[1],"the":[2,8,25,47,55,58,67,72,118,123,126,135,143,154,169,176,179,192],"quality":[3],"of":[4,11,27,50,57,71,125,178,191],"images,":[5,73],"resulting":[6],"in":[7,30,116,182],"poor":[9,48],"performance":[10,26,124],"many":[12],"image":[13],"processing":[14],"applications.":[15],"This":[16],"paper":[17],"presents":[18],"an":[19,74],"accurate":[20],"denoising":[21,60,117,183],"method":[22,105,181],"to":[23,43,53,86,150,168],"improve":[24],"human":[28],"detection":[29,136],"noisy":[31,96],"infrared":[32],"(IR)":[33],"images.":[34,88,98,120,172],"The":[35,89,99,173],"local":[36],"binary":[37],"pattern":[38],"(LBP)":[39],"detector":[40,91,128],"is":[41,63,129],"used":[42],"study":[44],"and":[45,52,82,102,109,152,159],"analyze":[46],"effects":[49],"noise":[51],"test":[54],"efficiency":[56,177],"proposed":[59,180],"method.":[61],"removed":[64],"by":[65],"minimizing":[66],"total":[68],"variation":[69],"(TV)":[70],"application":[75],"that":[76],"uses":[77],"partial":[78],"differential":[79],"equations":[80],"(PDEs)":[81],"optimal":[83],"numerical":[84],"methods":[85,113],"denoise":[87],"LBP":[90,127,193],"shows":[92],"abnormal":[93],"behavior":[94],"with":[95,166],"IR":[97,119,171,184],"Rudin,":[100],"Osher,":[101],"Fatemi":[103],"(ROF)":[104],"based":[106],"on":[107],"TV":[108,110],"norm1":[111],"(TV-L1)":[112],"are":[114,164],"efficient":[115],"In":[121],"addition,":[122],"improved.":[130],"Denoising":[131],"using":[132],"ROF":[133],"improves":[134],"results":[137,174],"efficiently":[138],"as":[139,186,188],"well.":[140],"Measures":[141],"for":[142],"true":[144],"positive":[145,161],"rate":[146],"increased":[147],"from":[148],"87%":[149],"89%,":[151],"both":[153],"false":[155,160],"negative":[156],"per":[157,162],"frame":[158,163],"decreased":[165],"respect":[167],"clear":[170],"prove":[175],"images":[185],"well":[187],"restoring":[189],"most":[190],"texture":[194],"features.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
