{"id":"https://openalex.org/W2149888236","doi":"https://doi.org/10.1109/igarss.2007.4422754","title":"Analysis of non-Gaussian POLSAR data","display_name":"Analysis of non-Gaussian POLSAR data","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2149888236","doi":"https://doi.org/10.1109/igarss.2007.4422754","mag":"2149888236"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2007.4422754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2007.4422754","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/A5034411171","display_name":"Anthony P. Doulgeris","orcid":"https://orcid.org/0000-0002-9345-6896"},"institutions":[{"id":"https://openalex.org/I78037679","display_name":"UiT The Arctic University of Norway","ror":"https://ror.org/00wge5k78","country_code":"NO","type":"education","lineage":["https://openalex.org/I78037679"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Anthony Doulgeris","raw_affiliation_strings":["Department of Physics and Technology, University of Troms\u00f8, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics and Technology, University of Troms\u00f8, Norway","institution_ids":["https://openalex.org/I78037679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019438000","display_name":"Stian Normann Anfinsen","orcid":"https://orcid.org/0000-0002-3758-4295"},"institutions":[{"id":"https://openalex.org/I78037679","display_name":"UiT The Arctic University of Norway","ror":"https://ror.org/00wge5k78","country_code":"NO","type":"education","lineage":["https://openalex.org/I78037679"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Stian Normann Anfinsen","raw_affiliation_strings":["Department of Physics and Technology, University of Troms\u00f8, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics and Technology, University of Troms\u00f8, Norway","institution_ids":["https://openalex.org/I78037679"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016021299","display_name":"Torbj\u00f8rn Eltoft","orcid":"https://orcid.org/0000-0002-1597-4364"},"institutions":[{"id":"https://openalex.org/I78037679","display_name":"UiT The Arctic University of Norway","ror":"https://ror.org/00wge5k78","country_code":"NO","type":"education","lineage":["https://openalex.org/I78037679"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Torbjorn Eltoft","raw_affiliation_strings":["Department of Physics and Technology, University of Troms\u00f8, Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics and Technology, University of Troms\u00f8, Norway","institution_ids":["https://openalex.org/I78037679"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78037679"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.18784778,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"160","last_page":"163"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9998999834060669,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9866999983787537,"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9776999950408936,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/wishart-distribution","display_name":"Wishart distribution","score":0.9851267337799072},{"id":"https://openalex.org/keywords/inverse-wishart-distribution","display_name":"Inverse-Wishart distribution","score":0.7093969583511353},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5727503299713135},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5650467872619629},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.524491012096405},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5196479558944702},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5188249945640564},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4998152256011963},{"id":"https://openalex.org/keywords/multivariate-normal-distribution","display_name":"Multivariate normal distribution","score":0.4755646586418152},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4383953809738159},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4311855733394623},{"id":"https://openalex.org/keywords/matrix-t-distribution","display_name":"Matrix t-distribution","score":0.41034987568855286},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.335703581571579},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29803746938705444},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24200299382209778},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2076292335987091},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20080995559692383},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08227884769439697}],"concepts":[{"id":"https://openalex.org/C33962027","wikidata":"https://www.wikidata.org/wiki/Q1930697","display_name":"Wishart distribution","level":3,"score":0.9851267337799072},{"id":"https://openalex.org/C40851411","wikidata":"https://www.wikidata.org/wiki/Q3258368","display_name":"Inverse-Wishart distribution","level":4,"score":0.7093969583511353},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5727503299713135},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5650467872619629},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.524491012096405},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5196479558944702},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5188249945640564},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4998152256011963},{"id":"https://openalex.org/C177384507","wikidata":"https://www.wikidata.org/wiki/Q1149000","display_name":"Multivariate normal distribution","level":3,"score":0.4755646586418152},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4383953809738159},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4311855733394623},{"id":"https://openalex.org/C43514536","wikidata":"https://www.wikidata.org/wiki/Q17098779","display_name":"Matrix t-distribution","level":4,"score":0.41034987568855286},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.335703581571579},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29803746938705444},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24200299382209778},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2076292335987091},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20080995559692383},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08227884769439697},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2007.4422754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2007.4422754","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"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.714.221","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.714.221","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://eo.uit.no/publications/APD-IGARSS-07.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W47994413","https://openalex.org/W1996176293","https://openalex.org/W2022725103","https://openalex.org/W2037095848","https://openalex.org/W2122878908","https://openalex.org/W2130762895","https://openalex.org/W2147004337","https://openalex.org/W2150705511","https://openalex.org/W2164296623","https://openalex.org/W2905233554","https://openalex.org/W6678607405"],"related_works":["https://openalex.org/W2489708607","https://openalex.org/W1987270193","https://openalex.org/W1981092891","https://openalex.org/W4248673206","https://openalex.org/W3016315862","https://openalex.org/W2021128345","https://openalex.org/W3134381438","https://openalex.org/W4252020916","https://openalex.org/W2240092503","https://openalex.org/W2120350343"],"abstract_inverted_index":{"In":[0],"this":[1,67,91],"paper":[2],"we":[3,98],"present":[4,66],"a":[5,11,59,100],"generalised":[6],"Wishart":[7,63],"classifier":[8],"derived":[9],"from":[10],"non-Gaussian":[12],"model":[13,35,55],"for":[14,38,52,79],"polarimetric":[15],"synthetic":[16],"aperture":[17],"radar":[18],"(POLSAR)":[19],"data.":[20,41,122],"Our":[21],"starting":[22],"point":[23],"is":[24,36,56,117],"to":[25],"demonstrate":[26],"that":[27,44],"the":[28,45,48,53,62,75,86,95],"scale":[29],"mixture":[30],"of":[31,47,61],"Gaussian":[32],"(SMoG)":[33],"distribution":[34,46],"suitable":[37],"modelling":[39],"POLSAR":[40],"We":[42,72],"show":[43],"sample":[49],"covariance":[50],"matrix":[51],"SMoG":[54,82],"given":[57],"as":[58,85],"generalisation":[60],"distribution,":[64,83,93,97],"and":[65,111,115],"expression":[68],"in":[69,108],"integral":[70],"form.":[71],"then":[73],"derive":[74],"closed":[76],"form":[77],"solution":[78],"one":[80],"particular":[81],"known":[84],"multivariate":[87],"K-distribution.":[88],"Based":[89],"on":[90,119],"new":[92],"termed":[94],"K-Wishart":[96],"propose":[99],"Bayesian":[101],"classification":[102,116],"scheme,":[103],"which":[104],"can":[105],"be":[106],"used":[107],"both":[109],"supervised":[110],"unsupervised":[112],"mode.":[113],"Modelling":[114],"tested":[118],"airborne":[120],"EMISAR":[121]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
