{"id":"https://openalex.org/W2969010916","doi":"https://doi.org/10.1109/rose.2019.8790426","title":"Comparative Analysis of Image Fusion Methods in Marine Environment","display_name":"Comparative Analysis of Image Fusion Methods in Marine Environment","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2969010916","doi":"https://doi.org/10.1109/rose.2019.8790426","mag":"2969010916"},"language":"en","primary_location":{"id":"doi:10.1109/rose.2019.8790426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rose.2019.8790426","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Robotic and Sensors Environments (ROSE)","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/A5079295224","display_name":"Fahimeh Farahnakian","orcid":null},"institutions":[{"id":"https://openalex.org/I155660961","display_name":"University of Turku","ror":"https://ror.org/05vghhr25","country_code":"FI","type":"education","lineage":["https://openalex.org/I155660961"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Fahimeh Farahnakian","raw_affiliation_strings":["Department of Future Technologies, University of Turku, Turku, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Future Technologies, University of Turku, Turku, Finland","institution_ids":["https://openalex.org/I155660961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071375864","display_name":"Parisa Movahedi","orcid":"https://orcid.org/0000-0002-2571-9279"},"institutions":[{"id":"https://openalex.org/I155660961","display_name":"University of Turku","ror":"https://ror.org/05vghhr25","country_code":"FI","type":"education","lineage":["https://openalex.org/I155660961"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Parisa Movahedi","raw_affiliation_strings":["Department of Future Technologies, University of Turku, Turku, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Future Technologies, University of Turku, Turku, Finland","institution_ids":["https://openalex.org/I155660961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068173798","display_name":"Jussi Poikonen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jussi Poikonen","raw_affiliation_strings":["Kongsberg Maritime Oy Ab, Turku, Finland"],"affiliations":[{"raw_affiliation_string":"Kongsberg Maritime Oy Ab, Turku, Finland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101635900","display_name":"Eero Lehtonen","orcid":"https://orcid.org/0000-0002-7327-7938"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eero Lehtonen","raw_affiliation_strings":["Kongsberg Maritime Oy Ab, Turku, Finland"],"affiliations":[{"raw_affiliation_string":"Kongsberg Maritime Oy Ab, Turku, Finland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057370857","display_name":"Dimitrios Makris","orcid":"https://orcid.org/0000-0001-6170-0236"},"institutions":[{"id":"https://openalex.org/I4210154901","display_name":"Kingston University","ror":"https://ror.org/0517ce304","country_code":"US","type":"education","lineage":["https://openalex.org/I4210154901"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dimitrios Makris","raw_affiliation_strings":["Faculty of Science, Engineering annd Computing, Kingston University, London"],"affiliations":[{"raw_affiliation_string":"Faculty of Science, Engineering annd Computing, Kingston University, London","institution_ids":["https://openalex.org/I4210154901"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058539829","display_name":"Jukka Heikkonen","orcid":"https://orcid.org/0000-0002-2468-5708"},"institutions":[{"id":"https://openalex.org/I155660961","display_name":"University of Turku","ror":"https://ror.org/05vghhr25","country_code":"FI","type":"education","lineage":["https://openalex.org/I155660961"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Jukka Heikkonen","raw_affiliation_strings":["Department of Future Technologies, University of Turku, Turku, Finland"],"affiliations":[{"raw_affiliation_string":"Department of Future Technologies, University of Turku, Turku, Finland","institution_ids":["https://openalex.org/I155660961"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5079295224"],"corresponding_institution_ids":["https://openalex.org/I155660961"],"apc_list":null,"apc_paid":null,"fwci":1.2498,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.82830265,"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":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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":0.9976000189781189,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.7768104672431946},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.695141613483429},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6758182644844055},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5814592838287354},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5366828441619873},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.47447019815444946},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4691941440105438},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.45787355303764343},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4250054657459259},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3987518846988678}],"concepts":[{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.7768104672431946},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.695141613483429},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6758182644844055},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5814592838287354},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5366828441619873},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.47447019815444946},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4691941440105438},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.45787355303764343},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4250054657459259},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3987518846988678},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rose.2019.8790426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rose.2019.8790426","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Symposium on Robotic and Sensors Environments (ROSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","score":0.8600000143051147,"id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1708141795","https://openalex.org/W1861492603","https://openalex.org/W1885185971","https://openalex.org/W1965606870","https://openalex.org/W1979211583","https://openalex.org/W1980382026","https://openalex.org/W1991084701","https://openalex.org/W2040833130","https://openalex.org/W2088173505","https://openalex.org/W2091484864","https://openalex.org/W2116702374","https://openalex.org/W2133665775","https://openalex.org/W2155243555","https://openalex.org/W2231495490","https://openalex.org/W2400972628","https://openalex.org/W2532801510","https://openalex.org/W2552737937","https://openalex.org/W2559870345","https://openalex.org/W2589745805","https://openalex.org/W2610070095","https://openalex.org/W2736611505","https://openalex.org/W2798018774","https://openalex.org/W2962835968","https://openalex.org/W2963446712","https://openalex.org/W3102515681","https://openalex.org/W3105639468","https://openalex.org/W6637373629","https://openalex.org/W6641606800","https://openalex.org/W6786337149"],"related_works":["https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3214791684","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2549658594","https://openalex.org/W2370195708","https://openalex.org/W1490651872"],"abstract_inverted_index":{"Image":[0,85],"fusion":[1,23,66,136,149,156],"methods":[2,150],"have":[3],"gained":[4],"a":[5,90,94,112,128,140],"lot":[6],"of":[7,17,51,59,75,114,122,131],"attraction":[8],"over":[9],"the":[10,15,35,57,97,120,154,160],"past":[11],"few":[12],"years":[13],"in":[14,96,111,139],"field":[16],"sensor":[18,91],"fusion.":[19],"An":[20],"efficient":[21],"image":[22,37,65,135,155],"approach":[24],"can":[25,151],"obtain":[26],"complementary":[27],"information":[28],"from":[29],"various":[30],"multi-modality":[31],"images.":[32,72],"In":[33],"addition,":[34],"fused":[36],"is":[38,54,78,102,126],"more":[39],"robust":[40],"to":[41,55],"imperfect":[42],"conditions":[43],"such":[44],"as":[45],"mis-registration":[46],"and":[47,63,108,116,133,163],"noise.":[48],"The":[49,73],"aim":[50],"this":[52],"paper":[53],"explore":[56],"performance":[58,74,157],"existing":[60],"deep":[61,147],"learning-based":[62,148],"traditional":[64],"techniques":[67,77],"for":[68,104],"our":[69,123],"real":[70],"marine":[71,141],"these":[76],"evaluated":[79,138],"with":[80,168],"six":[81],"common":[82],"quality":[83,162],"metrics.":[84],"data":[86,110],"was":[87],"collected":[88],"using":[89],"system":[92,101],"onboard":[93],"vessel":[95],"Finnish":[98],"archipelago.":[99],"This":[100],"used":[103],"developing":[105],"autonomous":[106],"vessels,":[107],"records":[109],"range":[113],"operation":[115],"climatic":[117],"conditions.":[118],"To":[119],"best":[121],"knowledge,":[124],"there":[125],"not":[127],"comparative":[129],"study":[130],"RGB":[132],"infrared":[134],"algorithms":[137],"environment.":[142],"Experimental":[143],"results":[144],"indicate":[145],"that":[146],"significantly":[152],"improve":[153],"considering":[158],"both":[159],"visual":[161],"objective":[164],"assessment":[165],"comparison":[166],"against":[167],"other":[169],"methods.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}