{"id":"https://openalex.org/W2171405598","doi":"https://doi.org/10.1109/igarss.2007.4423315","title":"Comparison of similarity measures of multi-sensor images for change detection applications","display_name":"Comparison of similarity measures of multi-sensor images for change detection applications","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2171405598","doi":"https://doi.org/10.1109/igarss.2007.4423315","mag":"2171405598"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2007.4423315","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2007.4423315","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Geoscience and Remote Sensing Symposium","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/A5042121085","display_name":"Vito Alberga","orcid":null},"institutions":[{"id":"https://openalex.org/I150517870","display_name":"Royal Military Academy","ror":"https://ror.org/02vmnye06","country_code":"BE","type":"education","lineage":["https://openalex.org/I150517870"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"V. Alberga","raw_affiliation_strings":["Signal and Image Centre, Royal Military Academy, Brussels, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal and Image Centre, Royal Military Academy, Brussels, Belgium","institution_ids":["https://openalex.org/I150517870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074453543","display_name":"Mahamadou Idrissa","orcid":null},"institutions":[{"id":"https://openalex.org/I150517870","display_name":"Royal Military Academy","ror":"https://ror.org/02vmnye06","country_code":"BE","type":"education","lineage":["https://openalex.org/I150517870"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"M. Idrissa","raw_affiliation_strings":["Signal and Image Centre, Royal Military Academy, Brussels, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal and Image Centre, Royal Military Academy, Brussels, Belgium","institution_ids":["https://openalex.org/I150517870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110445017","display_name":"Val\u00e9rie Lacroix","orcid":null},"institutions":[{"id":"https://openalex.org/I150517870","display_name":"Royal Military Academy","ror":"https://ror.org/02vmnye06","country_code":"BE","type":"education","lineage":["https://openalex.org/I150517870"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"V. Lacroix","raw_affiliation_strings":["Signal and Image Centre, Royal Military Academy, Brussels, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal and Image Centre, Royal Military Academy, Brussels, Belgium","institution_ids":["https://openalex.org/I150517870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075135845","display_name":"Jordi Inglada","orcid":"https://orcid.org/0000-0001-6896-0049"},"institutions":[{"id":"https://openalex.org/I2801994115","display_name":"European Space Agency","ror":"https://ror.org/03wd9za21","country_code":"FR","type":"funder","lineage":["https://openalex.org/I2801994115"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"J. Inglada","raw_affiliation_strings":["DCT/SI/AP, bpi 1219, French Space Agency (CNES), Toulouse, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DCT/SI/AP, bpi 1219, French Space Agency (CNES), Toulouse, France","institution_ids":["https://openalex.org/I2801994115"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2358","last_page":"2361"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.909500002861023,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/change-detection","display_name":"Change detection","score":0.886949896812439},{"id":"https://openalex.org/keywords/radiometry","display_name":"Radiometry","score":0.6862250566482544},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6632227897644043},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6185304522514343},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6035083532333374},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.5819816589355469},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5647861361503601},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5028261542320251},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4274366497993469},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4113006591796875},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.39723604917526245},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38345932960510254},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3472893238067627},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2120514214038849},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15043208003044128},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12214282155036926}],"concepts":[{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.886949896812439},{"id":"https://openalex.org/C87456703","wikidata":"https://www.wikidata.org/wiki/Q247760","display_name":"Radiometry","level":2,"score":0.6862250566482544},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6632227897644043},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6185304522514343},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6035083532333374},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.5819816589355469},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5647861361503601},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5028261542320251},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4274366497993469},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4113006591796875},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.39723604917526245},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38345932960510254},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3472893238067627},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2120514214038849},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15043208003044128},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12214282155036926}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2007.4423315","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2007.4423315","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2114425704","https://openalex.org/W2121005491","https://openalex.org/W2123000132","https://openalex.org/W2128559984","https://openalex.org/W2145565958","https://openalex.org/W2153696326","https://openalex.org/W2165021910"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W1995114632","https://openalex.org/W2376528221","https://openalex.org/W196800607","https://openalex.org/W2359428812","https://openalex.org/W3181296946","https://openalex.org/W2085033728","https://openalex.org/W4285411112"],"abstract_inverted_index":{"Change":[0],"detection":[1,77,105],"of":[2,58,71,94,112,118,122,128,134,139],"remotely":[3],"sensed":[4],"images":[5,90],"is":[6,52],"a":[7,92],"particularly":[8],"challenging":[9],"task":[10],"when":[11,39],"the":[12,40,56,102,119,123,126,129,132,135,140,144],"available":[13],"data":[14,41],"come":[15],"from":[16],"different":[17,46],"sensors.":[18],"Indeed,":[19],"many":[20],"change":[21,76,104],"indicators":[22,60],"are":[23,35],"based":[24],"on":[25,29,66],"radiometry":[26],"measures,":[27],"operating":[28],"their":[30,82],"differences":[31],"or":[32],"ratios,":[33],"that":[34,61,101,110],"no":[36],"longer":[37],"reliable":[38],"have":[42],"been":[43,79],"acquired":[44],"by":[45],"instruments.":[47],"For":[48],"this":[49],"reason,":[50],"it":[51],"interesting":[53],"to":[54],"study":[55],"performance":[57,84],"those":[59],"do":[62],"not":[63],"rely":[64],"completely":[65],"radiometric":[67],"values.":[68],"A":[69],"series":[70],"similarity":[72,141],"measures":[73],"for":[74,131],"automatic":[75],"has":[78],"investigated":[80],"and":[81,88,138],"general":[83],"compared":[85],"using":[86],"optical":[87],"SAR":[89],"covering":[91],"period":[93],"about":[95],"six":[96],"years.":[97],"We":[98],"could":[99],"observe":[100],"considered":[103],"algorithms":[106],"perform":[107],"differently":[108],"but":[109],"none":[111],"them":[113],"permits":[114],"an":[115],"\"absolute\"":[116],"measure":[117],"changes":[120],"independent":[121],"sensor.":[124],"Also":[125],"dimensions":[127],"windows,":[130],"estimation":[133],"pixel":[136],"statistics":[137],"measure,":[142],"affect":[143],"final":[145],"results.":[146]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
