{"id":"https://openalex.org/W4308234210","doi":"https://doi.org/10.1109/icip46576.2022.9897608","title":"Dynamic Mutual Enhancement Network for Single Remote Sensing Image Dehazing","display_name":"Dynamic Mutual Enhancement Network for Single Remote Sensing Image Dehazing","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308234210","doi":"https://doi.org/10.1109/icip46576.2022.9897608"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897608","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897608","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","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/A5100388412","display_name":"Shan Wang","orcid":"https://orcid.org/0000-0001-5991-5254"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shan Wang","raw_affiliation_strings":["Beijing Normal University,School of Artificial Intelligence,Beijing,China,100875"],"affiliations":[{"raw_affiliation_string":"Beijing Normal University,School of Artificial Intelligence,Beijing,China,100875","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087779583","display_name":"Libao Zhang","orcid":"https://orcid.org/0000-0002-0888-2330"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Libao Zhang","raw_affiliation_strings":["Beijing Normal University,School of Artificial Intelligence,Beijing,China,100875"],"affiliations":[{"raw_affiliation_string":"Beijing Normal University,School of Artificial Intelligence,Beijing,China,100875","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100388412"],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":null,"apc_paid":null,"fwci":0.4198,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.70904035,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3336","last_page":"3340"},"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":0.9988999962806702,"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":0.998199999332428,"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/computer-science","display_name":"Computer science","score":0.8261454105377197},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.7303344011306763},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6619682908058167},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5279908180236816},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5122353434562683},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4206423759460449},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4056243896484375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8261454105377197},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.7303344011306763},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6619682908058167},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5279908180236816},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5122353434562683},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4206423759460449},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4056243896484375},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/icip46576.2022.9897608","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897608","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2097900287","https://openalex.org/W2113850718","https://openalex.org/W2128254161","https://openalex.org/W2133665775","https://openalex.org/W2141983208","https://openalex.org/W2156936307","https://openalex.org/W2256362396","https://openalex.org/W2331128040","https://openalex.org/W2476548250","https://openalex.org/W2779176852","https://openalex.org/W2891158090","https://openalex.org/W2901543290","https://openalex.org/W2962754725","https://openalex.org/W2963372104","https://openalex.org/W2966926453","https://openalex.org/W2990007814","https://openalex.org/W2998249728","https://openalex.org/W3015557838","https://openalex.org/W3015578900","https://openalex.org/W3144549167","https://openalex.org/W3173269149","https://openalex.org/W3193565959","https://openalex.org/W3195087825","https://openalex.org/W4205873333"],"related_works":["https://openalex.org/W2466816617","https://openalex.org/W1970834875","https://openalex.org/W3174028392","https://openalex.org/W842936808","https://openalex.org/W2047973478","https://openalex.org/W4295532600","https://openalex.org/W2000517284","https://openalex.org/W2136503713","https://openalex.org/W2365318811","https://openalex.org/W2063823869"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,49,52,58,78],"dynamic":[6,59,64],"mutual":[7,60,65,79],"enhancement":[8,66],"network":[9,109],"(DMENet)":[10],"for":[11,108],"haze":[12],"removal":[13],"in":[14,77],"remote":[15,138],"sensing":[16,139],"images.":[17],"It":[18],"has":[19],"three":[20,46],"major":[21],"advantages":[22],"compared":[23],"with":[24],"other":[25],"dehazing":[26],"algorithms:":[27],"1)":[28],"The":[29,63],"proposed":[30,145],"DMENet":[31,146],"is":[32,43,69,106],"based":[33],"on":[34,132],"the":[35,83,95,101,103,112,122,144,152],"U-Net":[36],"architecture":[37],"to":[38,71],"extract":[39],"features":[40],"effectively,":[41],"which":[42,81,119],"composed":[44],"of":[45,100,121],"components,":[47],"i.e.,":[48],"multi-scale":[50],"encoder,":[51],"middle":[53],"transmission":[54],"layer":[55],"(MTL),":[56],"and":[57,87,97,115,127,136],"decoder.":[61],"2)":[62],"(DME)":[67],"module":[68],"designed":[70],"dynamically":[72],"integrate":[73],"multi-level":[74],"feature":[75],"maps":[76],"way,":[80],"contains":[82],"low-level":[84],"detail":[85],"information":[86,90],"high-level":[88],"semantic":[89],"respectively.":[91],"3)":[92],"To":[93],"improve":[94],"robustness":[96],"generalization":[98],"performance":[99],"DMENet,":[102],"hybrid":[104],"supervision":[105,126],"built":[107],"training":[110],"between":[111],"restored":[113],"results":[114,131],"their":[116],"ground-truth":[117],"labels,":[118],"consists":[120],"pixel-level":[123],"supervision,":[124],"patch-level":[125],"image-level":[128],"supervision.":[129],"Experimental":[130],"both":[133],"synthetic":[134],"datasets":[135],"real":[137],"hazy":[140],"images":[141],"demonstrate":[142],"that":[143],"can":[147],"gain":[148],"significant":[149],"progresses":[150],"over":[151],"competing":[153],"methods.":[154]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}