{"id":"https://openalex.org/W2102868250","doi":"https://doi.org/10.1109/igarss.2004.1368681","title":"An approach to unsupervised change detection in multitemporal SAR images based on the generalized Gaussian distribution","display_name":"An approach to unsupervised change detection in multitemporal SAR images based on the generalized Gaussian distribution","publication_year":2004,"publication_date":"2004-12-23","ids":{"openalex":"https://openalex.org/W2102868250","doi":"https://doi.org/10.1109/igarss.2004.1368681","mag":"2102868250"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2004.1368681","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2004.1368681","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004","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/A5054237841","display_name":"Yakoub Bazi","orcid":"https://orcid.org/0000-0001-9287-0596"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Y. Bazi","raw_affiliation_strings":["Department of Information and Communication Technologies, University of Trento, Trento, Italy","Dept. of Information & Commun. Technol., Trento Univ., Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Technologies, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Dept. of Information & Commun. Technol., Trento Univ., Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006095323","display_name":"Lorenzo Bruzzone","orcid":"https://orcid.org/0000-0002-6036-459X"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"L. Bruzzone","raw_affiliation_strings":["Department of Information and Communication Technologies, University of Trento, Trento, Italy","Dept. of Information & Commun. Technol., Trento Univ., Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Technologies, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Dept. of Information & Commun. Technol., Trento Univ., Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021389231","display_name":"Farid Melgani","orcid":"https://orcid.org/0000-0001-9745-3732"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"F. Melgani","raw_affiliation_strings":["Department of Information and Communication Technologies, University of Trento, Trento, Italy","Dept. of Information & Commun. Technol., Trento Univ., Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Technologies, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Dept. of Information & Commun. Technol., Trento Univ., Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054237841"],"corresponding_institution_ids":["https://openalex.org/I193223587"],"apc_list":null,"apc_paid":null,"fwci":2.7219,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.90647566,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"2","issue":null,"first_page":"1402","last_page":"1405"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9879000186920166,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9865000247955322,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.7838737964630127},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7027583718299866},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.625095784664154},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6128422021865845},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5960910320281982},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5589167475700378},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5170046091079712},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4944722652435303},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.48871684074401855},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4883532226085663},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.473161518573761},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3826060891151428}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7838737964630127},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7027583718299866},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.625095784664154},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6128422021865845},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5960910320281982},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5589167475700378},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5170046091079712},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4944722652435303},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.48871684074401855},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4883532226085663},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.473161518573761},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3826060891151428},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2004.1368681","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2004.1368681","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.unitn.it:11572/78603","is_oa":false,"landing_page_url":"http://hdl.handle.net/11572/78603","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2027091505","https://openalex.org/W2102272668","https://openalex.org/W2106052468","https://openalex.org/W2110519070","https://openalex.org/W2160544350","https://openalex.org/W2333375553"],"related_works":["https://openalex.org/W2065648684","https://openalex.org/W2009383287","https://openalex.org/W2164995725","https://openalex.org/W2042914788","https://openalex.org/W2182190754","https://openalex.org/W4321264664","https://openalex.org/W2055824452","https://openalex.org/W2121688719","https://openalex.org/W2727313114","https://openalex.org/W2016481886"],"abstract_inverted_index":{"This":[0,14],"paper":[1],"presents":[2],"a":[3,37,57,86,106,110,142],"novel":[4,107],"approach":[5,15],"to":[6,36,62,76,84,105],"unsupervised":[7],"change":[8],"detection":[9],"in":[10,56,60,82],"multitemporal":[11,33,143],"SAR":[12,144],"images.":[13],"is":[16,74,112,124],"based":[17,25,113],"on":[18,26,114,141],"three":[19],"main":[20],"steps:":[21],"(1)":[22],"controlled":[23,58],"preprocessing":[24],"adaptive":[27],"filtering":[28],"(despeckling);":[29],"(2)":[30],"comparison":[31],"between":[32,66],"images":[34,81],"according":[35,104],"proper":[38],"operator;":[39],"(3)":[40],"automatic":[41],"thresholding":[42,100,117],"of":[43,97,150],"the":[44,53,64,78,90,95,101,115,127,133,148,151],"log-ratio":[45,87,102],"image.":[46,88],"The":[47,71],"first":[48],"step":[49,73,92],"aims":[50],"at":[51],"reducing":[52],"speckle":[54],"noise":[55],"way":[59],"order":[61,83],"maximize":[63],"separability":[65],"changed":[67,134],"and":[68,135],"unchanged":[69,136],"classes.":[70,137],"second":[72],"devoted":[75],"compare":[77],"two":[79],"filtered":[80],"generate":[85],"Finally,":[89],"third":[91],"deals":[93],"with":[94],"identification":[96],"changes":[98],"by":[99],"image":[103],"technique.":[108],"Such":[109],"technique":[111],"double":[116],"Kittler":[118],"&":[119],"Illingworth":[120],"(K&I)":[121],"algorithm,":[122],"which":[123],"reformulated":[125],"under":[126],"Generalized":[128],"Gaussian":[129],"(GG)":[130],"assumption":[131],"for":[132],"Experimental":[138],"results":[139],"obtained":[140],"data":[145],"set":[146],"confirm":[147],"effectiveness":[149],"proposed":[152],"approach.":[153]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}