{"id":"https://openalex.org/W2592228376","doi":"https://doi.org/10.5220/0006132400770088","title":"Dehazing using Non-local Regularization with Iso-depth Neighbor-Fields","display_name":"Dehazing using Non-local Regularization with Iso-depth Neighbor-Fields","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2592228376","doi":"https://doi.org/10.5220/0006132400770088","mag":"2592228376"},"language":"en","primary_location":{"id":"doi:10.5220/0006132400770088","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0006132400770088","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0006132400770088","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066676430","display_name":"Incheol Kim","orcid":"https://orcid.org/0000-0002-5754-133X"},"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":true,"raw_author_name":"Incheol Kim","raw_affiliation_strings":["KAIST, Korea, Republic of"],"affiliations":[{"raw_affiliation_string":"KAIST, Korea, Republic of","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052213409","display_name":"Min H. Kim","orcid":"https://orcid.org/0000-0002-5078-4005"},"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":"Min H. Kim","raw_affiliation_strings":["KAIST, Korea, Republic of"],"affiliations":[{"raw_affiliation_string":"KAIST, Korea, Republic of","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066676430"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.182,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.53996943,"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":null,"last_page":null},"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":0.9983999729156494,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9915000200271606,"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/haze","display_name":"Haze","score":0.9070218801498413},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.8610464930534363},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.6475337743759155},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6094853281974792},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5531144738197327},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.5024182796478271},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.47709283232688904},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4667314291000366},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36644890904426575},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3549965023994446},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3432692885398865},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.24453845620155334},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.12940430641174316},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.10945907235145569},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10557225346565247},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.06753367185592651}],"concepts":[{"id":"https://openalex.org/C79974267","wikidata":"https://www.wikidata.org/wiki/Q643546","display_name":"Haze","level":2,"score":0.9070218801498413},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.8610464930534363},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.6475337743759155},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6094853281974792},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5531144738197327},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.5024182796478271},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.47709283232688904},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4667314291000366},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36644890904426575},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3549965023994446},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3432692885398865},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.24453845620155334},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.12940430641174316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.10945907235145569},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10557225346565247},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.06753367185592651}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5220/0006132400770088","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0006132400770088","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.5220/0006132400770088","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0006132400770088","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.4399999976158142,"display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1488971909","https://openalex.org/W1554544485","https://openalex.org/W1971693194","https://openalex.org/W1991133427","https://openalex.org/W1993120651","https://openalex.org/W2028763589","https://openalex.org/W2028990532","https://openalex.org/W2035773017","https://openalex.org/W2065002911","https://openalex.org/W2081418206","https://openalex.org/W2097900287","https://openalex.org/W2099256125","https://openalex.org/W2108619558","https://openalex.org/W2110644821","https://openalex.org/W2114867966","https://openalex.org/W2121880036","https://openalex.org/W2128254161","https://openalex.org/W2130248603","https://openalex.org/W2133773881","https://openalex.org/W2143516773","https://openalex.org/W2147318913","https://openalex.org/W2156094048","https://openalex.org/W2156936307","https://openalex.org/W2206123561","https://openalex.org/W2467473805","https://openalex.org/W2536722097","https://openalex.org/W2912104034","https://openalex.org/W3151331431"],"related_works":["https://openalex.org/W2397673276","https://openalex.org/W2318437963","https://openalex.org/W2348696601","https://openalex.org/W2041196008","https://openalex.org/W2006843870","https://openalex.org/W1602455006","https://openalex.org/W2063548088","https://openalex.org/W2155863751","https://openalex.org/W2744800241","https://openalex.org/W1592969877"],"abstract_inverted_index":{"Removing":[0],"haze":[1,47,55,94,110,150,167,197],"from":[2,50,93],"a":[3,7,38,43,86,115,139,171],"single":[4],"image":[5,27,141],"is":[6,48,56,74,154],"severely":[8],"ill-posed":[9],"problem":[10],"due":[11],"to":[12,36,62,107,156,169,195],"the":[13,16,32,63,109,135,145,152,162,180],"lack":[14],"of":[15,65,173],"scene":[17,102],"information.":[18],"General":[19],"dehazing":[20,193],"algorithms":[21,194],"estimate":[22],"airlight":[23,35],"initially":[24],"using":[25],"natural":[26,174],"statistics":[28],"and":[29],"then":[30],"propagate":[31],"incompletely":[33],"estimated":[34],"build":[37],"dense":[39],"transmission":[40],"map,":[41],"yielding":[42],"haze-free":[44],"image.":[45],"Propagating":[46],"different":[49],"other":[51,192],"regularization":[52,83,117,184],"problems,":[53],"as":[54,148,177],"strongly":[57],"correlated":[58],"with":[59,85,125,190],"depth":[60,76],"according":[61],"physics":[64],"light":[66],"transport":[67],"in":[68,79,101,138,151,179],"participating":[69],"media.":[70],"However,":[71],"since":[72],"there":[73],"no":[75],"information":[77],"available":[78],"single-image":[80],"dehazing,":[81],"traditional":[82],"methods":[84],"common":[87],"grid":[88],"random":[89,122],"field":[90],"often":[91],"suffer":[92],"isolation":[95,111],"artifacts":[96],"caused":[97],"by":[98,119],"abrupt":[99],"changes":[100],"depths.":[103],"In":[104],"this":[105],"paper,":[106],"overcome":[108],"problem,":[112],"we":[113],"propose":[114],"non-local":[116],"method":[118,164,185],"combining":[120],"Markov":[121],"fields":[123,127],"(MRFs)":[124],"nearest-neighbor":[126],"(NNFs),":[128],"based":[129],"on":[130],"our":[131],"insightful":[132],"observation":[133],"that":[134,161],"NNFs":[136],"searched":[137],"hazy":[140],"associate":[142],"patches":[143],"at":[144],"similar":[146],"depth,":[147],"local":[149],"atmosphere":[153],"proportional":[155],"its":[157],"depth.":[158],"We":[159],"validate":[160],"proposed":[163,183],"can":[165,186],"regularize":[166],"effectively":[168],"restore":[170],"variety":[172],"landscape":[175],"images,":[176],"demonstrated":[178],"results.":[181],"This":[182],"be":[187],"used":[188],"separately":[189],"any":[191],"enhance":[196],"regularization.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}