{"id":"https://openalex.org/W7130377051","doi":"https://doi.org/10.1109/tencon66050.2025.11375016","title":"Dehazing Algorithm Selection System with Feature Extraction for Single Image","display_name":"Dehazing Algorithm Selection System with Feature Extraction for Single Image","publication_year":2025,"publication_date":"2025-10-27","ids":{"openalex":"https://openalex.org/W7130377051","doi":"https://doi.org/10.1109/tencon66050.2025.11375016"},"language":null,"primary_location":{"id":"doi:10.1109/tencon66050.2025.11375016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon66050.2025.11375016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2025 - 2025 IEEE Region 10 Conference (TENCON)","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/A5026193889","display_name":"Yuto Toyoshima","orcid":null},"institutions":[{"id":"https://openalex.org/I206011266","display_name":"Kwansei Gakuin University","ror":"https://ror.org/02qf2tx24","country_code":"JP","type":"education","lineage":["https://openalex.org/I206011266"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuto Toyoshima","raw_affiliation_strings":["Graduate School of Science and Engineering Kwansei Gakuin University Sanda,Hyogo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering Kwansei Gakuin University Sanda,Hyogo,Japan","institution_ids":["https://openalex.org/I206011266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010499178","display_name":"Keizo Miyahara","orcid":null},"institutions":[{"id":"https://openalex.org/I206011266","display_name":"Kwansei Gakuin University","ror":"https://ror.org/02qf2tx24","country_code":"JP","type":"education","lineage":["https://openalex.org/I206011266"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keizo Miyahara","raw_affiliation_strings":["Graduate School of Science and Engineering Kwansei Gakuin University Sanda,Hyogo,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering Kwansei Gakuin University Sanda,Hyogo,Japan","institution_ids":["https://openalex.org/I206011266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I206011266"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64241231,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"831","last_page":"834"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9437000155448914,"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":0.9437000155448914,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.006099999882280827,"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/T14319","display_name":"Currency Recognition and Detection","score":0.005200000014156103,"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/image","display_name":"Image (mathematics)","score":0.6046000123023987},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5878000259399414},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5446000099182129},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5175999999046326},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5044000148773193},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4593000113964081},{"id":"https://openalex.org/keywords/feature-detection","display_name":"Feature detection (computer vision)","score":0.45910000801086426},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.397599995136261}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.715499997138977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7111999988555908},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6046000123023987},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5879999995231628},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5878000259399414},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5446000099182129},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5175999999046326},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5044000148773193},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4593000113964081},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.45910000801086426},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.397599995136261},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3693999946117401},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C2775973920","wikidata":"https://www.wikidata.org/wiki/Q3252726","display_name":"Selection algorithm","level":3,"score":0.3598000109195709},{"id":"https://openalex.org/C3019635856","wikidata":"https://www.wikidata.org/wiki/Q1619726","display_name":"Background image","level":3,"score":0.34290000796318054},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34040001034736633},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.3163999915122986},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2994999885559082},{"id":"https://openalex.org/C62725073","wikidata":"https://www.wikidata.org/wiki/Q1771663","display_name":"Image histogram","level":5,"score":0.2985000014305115},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.28600001335144043},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.26010000705718994}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon66050.2025.11375016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon66050.2025.11375016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2025 - 2025 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7608884852","display_name":"\u30cf\u30cb\u30ab\u30e0\u753b\u7d20\u69cb\u9020\u3092\u6709\u30573\u8ef8\u96e2\u6563\u5ea7\u6a19\u7cfb\u3092\u6d3b\u7528\u3057\u305f\u753b\u50cf\u51e6\u7406\u7cfb","funder_award_id":"24K14832","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1525232438","https://openalex.org/W2049679017","https://openalex.org/W2098985238","https://openalex.org/W2125527601","https://openalex.org/W2128254161","https://openalex.org/W2164260113","https://openalex.org/W2262607787","https://openalex.org/W2293894573","https://openalex.org/W2765919417","https://openalex.org/W2936479322","https://openalex.org/W2963037989","https://openalex.org/W4403185642"],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,48,133],"selection":[4],"system":[5,129],"of":[6,20,31,50,85,135,145,151,160],"dehaze-algorithm":[7],"to":[8,42,70],"apply":[9],"an":[10,14],"appropriate":[11],"one":[12,30],"for":[13,36,76],"input":[15,78],"single":[16],"image":[17,38,79,87,118],"by":[18],"means":[19],"feature":[21,63],"extraction.":[22],"It":[23],"is":[24,29],"known":[25],"that":[26,156],"the":[27,32,45,68,72,77,82,86,146,149,152,158,161],"haze":[28],"most":[33,73],"critical":[34],"challenges":[35],"camera":[37],"processing.":[39],"In":[40],"order":[41],"cope":[43],"with":[44,67,117],"negative":[46],"effect,":[47],"number":[49],"dehazing":[51,60],"algorithms":[52,61,92],"have":[53],"been":[54],"researched.":[55],"Previous":[56],"studies":[57],"on":[58,81,102],"both":[59],"and":[62,114],"descriptors":[64],"were":[65],"examined":[66,90],"aim":[69],"select":[71],"suitable":[74],"algorithm":[75],"based":[80,101],"explicit":[83],"indices":[84],"itself.":[88],"The":[89,127,143],"dehaze":[91],"can":[93],"be":[94],"categorized":[95],"in":[96],"two":[97],"groups:":[98],"Image":[99,115],"restoration":[100],"physical":[103],"model":[104],"(GMRF,":[105],"Optical":[106],"filtering,":[107],"DCP,":[108],"Bayesian":[109],"net,":[110],"Pre-record":[111],"data":[112],"set)":[113],"improvement":[116,150],"parameters":[119],"(Wavelet,":[120],"Retinex,":[121],"High":[122],"frequency":[123],"enhancement,":[124],"Histogram":[125],"equalizing).":[126],"implemented":[128],"was":[130],"validated":[131],"through":[132],"series":[134],"object":[136],"detection":[137],"experiments":[138,147],"using":[139],"real-world":[140],"hazy":[141],"images.":[142],"results":[144],"confirmed":[148],"evaluation":[153],"metric,":[154],"mAP,":[155],"depicts":[157],"effectiveness":[159],"proposed":[162],"system.":[163]},"counts_by_year":[],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2026-02-19T00:00:00"}