{"id":"https://openalex.org/W3035489957","doi":"https://doi.org/10.1109/icme46284.2020.9102800","title":"Single Image Rain Removal Boosting Via Directional Gradient","display_name":"Single Image Rain Removal Boosting Via Directional Gradient","publication_year":2020,"publication_date":"2020-06-09","ids":{"openalex":"https://openalex.org/W3035489957","doi":"https://doi.org/10.1109/icme46284.2020.9102800","mag":"3035489957"},"language":"en","primary_location":{"id":"doi:10.1109/icme46284.2020.9102800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102800","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","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/A5031121165","display_name":"Wu Ran","orcid":"https://orcid.org/0000-0001-8478-0750"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wu Ran","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003695311","display_name":"Youzhao Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youzhao Yang","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070355771","display_name":"Hong Lu","orcid":"https://orcid.org/0000-0002-4572-2854"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Lu","raw_affiliation_strings":["Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":1.0252,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.83801054,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","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/T11019","display_name":"Image Enhancement Techniques","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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9980999827384949,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9972000122070312,"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/streak","display_name":"Streak","score":0.7911382913589478},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7172544598579407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5767019391059875},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4881154000759125},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4711006283760071},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4667656123638153},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.44772204756736755},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4422767758369446},{"id":"https://openalex.org/keywords/atmospheric-model","display_name":"Atmospheric model","score":0.432583212852478},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4302046298980713},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.4155784845352173},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4150053560733795},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3834868371486664},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3834455907344818},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3208562135696411},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.31482312083244324},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.1744196116924286},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16961142420768738},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1346249282360077}],"concepts":[{"id":"https://openalex.org/C65185188","wikidata":"https://www.wikidata.org/wiki/Q107775","display_name":"Streak","level":2,"score":0.7911382913589478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7172544598579407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5767019391059875},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4881154000759125},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4711006283760071},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4667656123638153},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.44772204756736755},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4422767758369446},{"id":"https://openalex.org/C118365302","wikidata":"https://www.wikidata.org/wiki/Q4817115","display_name":"Atmospheric model","level":2,"score":0.432583212852478},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4302046298980713},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.4155784845352173},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4150053560733795},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3834868371486664},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3834455907344818},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3208562135696411},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.31482312083244324},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.1744196116924286},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16961142420768738},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1346249282360077},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199289684","wikidata":"https://www.wikidata.org/wiki/Q83353","display_name":"Mineralogy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme46284.2020.9102800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme46284.2020.9102800","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multimedia and Expo (ICME)","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":32,"referenced_works":["https://openalex.org/W2108565186","https://openalex.org/W2133665775","https://openalex.org/W2142058898","https://openalex.org/W2209874411","https://openalex.org/W2466666260","https://openalex.org/W2559264300","https://openalex.org/W2596372226","https://openalex.org/W2617199345","https://openalex.org/W2740982616","https://openalex.org/W2777170053","https://openalex.org/W2777241530","https://openalex.org/W2778532031","https://openalex.org/W2789288870","https://openalex.org/W2884068670","https://openalex.org/W2888632407","https://openalex.org/W2903613130","https://openalex.org/W2904219393","https://openalex.org/W2930755307","https://openalex.org/W2963017889","https://openalex.org/W2963641969","https://openalex.org/W2963800716","https://openalex.org/W2964212750","https://openalex.org/W2966083079","https://openalex.org/W2981380309","https://openalex.org/W3011279612","https://openalex.org/W3098038213","https://openalex.org/W6747017484","https://openalex.org/W6747362942","https://openalex.org/W6753755972","https://openalex.org/W6756590841","https://openalex.org/W6756715488","https://openalex.org/W6967015580"],"related_works":["https://openalex.org/W2082818786","https://openalex.org/W2000740899","https://openalex.org/W2371834895","https://openalex.org/W2997637732","https://openalex.org/W2381571063","https://openalex.org/W2090450991","https://openalex.org/W213647845","https://openalex.org/W2047678803","https://openalex.org/W2362555026","https://openalex.org/W4255171458"],"abstract_inverted_index":{"Image":[0],"rain":[1,38,55,88,95,108],"removal":[2],"has":[3],"been":[4],"widely":[5],"studied":[6],"with":[7,36,141],"traditional":[8,17],"methods":[9,13,18,26],"and":[10,23,30,51,79,106,123],"learning":[11,25,144],"based":[12,82,145],"for":[14,85],"years.":[15],"However,":[16],"like":[19],"Gaussian":[20],"mixture":[21],"model":[22,103,120],"dictionary":[24],"are":[27,43],"time":[28],"consuming":[29],"fail":[31],"to":[32,99,104],"well":[33,61],"tackle":[34],"images":[35],"heavy":[37,107],"streaks":[39,96],"since":[40],"image":[41,87],"patches":[42],"severely":[44],"contaminated.":[45],"By":[46],"considering":[47],"the":[48,101,118,133,142],"line-like":[49],"property":[50],"angle":[52],"distribution":[53],"of":[54,72,94],"streaks,":[56],"this":[57,64],"problem":[58],"can":[59],"be":[60],"solved.":[62],"In":[63],"paper,":[65],"by":[66],"introducing":[67],"Directional":[68],"b":[69],"radient":[70],"operator":[71],"arbitrary":[73],"direction,":[74],"we":[75],"propose":[76],"an":[77],"efficient":[78],"robust":[80],"Constraints":[81],"Model":[83],"(DiG-CoM)":[84],"single":[86],"removal.":[89],"Moreover,":[90],"a":[91],"density":[92],"metric":[93],"is":[97,150],"applied":[98],"generalize":[100],"proposed":[102,119,134],"light":[105],"streak":[109],"occasions.":[110],"Extensive":[111],"experiments":[112],"on":[113,130],"synthetic":[114],"datasets":[115],"demonstrate":[116],"that":[117],"outperforms":[121],"GMM":[122],"JCAS":[124],"while":[125],"requiring":[126],"less":[127],"time.":[128],"Furthermore,":[129],"real-world":[131],"occasions,":[132],"method":[135],"obtains":[136],"better":[137],"generalization":[138],"ability":[139],"compared":[140],"stateof-the-art":[143],"methods.":[146],"The":[147],"source":[148],"code":[149],"available":[151],"at":[152],"https://github.com/Schizophreni/Set-vanish-to-the-rain.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}