{"id":"https://openalex.org/W3085801037","doi":"https://doi.org/10.1109/lgrs.2020.3034700","title":"PolSAR Image Classification Based on Robust Low-Rank Feature Extraction and Markov Random Field","display_name":"PolSAR Image Classification Based on Robust Low-Rank Feature Extraction and Markov Random Field","publication_year":2020,"publication_date":"2020-11-09","ids":{"openalex":"https://openalex.org/W3085801037","doi":"https://doi.org/10.1109/lgrs.2020.3034700","mag":"3085801037"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2020.3034700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2020.3034700","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5039966032","display_name":"Haixia Bi","orcid":"https://orcid.org/0009-0003-2879-0550"},"institutions":[{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Haixia Bi","raw_affiliation_strings":["Faculty of Engineering, University of Bristol, Bristol, U.K"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Bristol, Bristol, U.K","institution_ids":["https://openalex.org/I36234482"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013885739","display_name":"Jing Yao","orcid":"https://orcid.org/0000-0003-1301-9758"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Yao","raw_affiliation_strings":["School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China","School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074077175","display_name":"Zhiqiang Wei","orcid":"https://orcid.org/0000-0003-3400-5590"},"institutions":[{"id":"https://openalex.org/I4210135667","display_name":"Xian Mechanical & Electric Institute (China)","ror":"https://ror.org/04d9wma96","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210135667"]},{"id":"https://openalex.org/I4210141776","display_name":"China XD Group (China)","ror":"https://ror.org/04ceqst84","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210141776"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Wei","raw_affiliation_strings":["Xi’an Electronics and Engineering Institute, Xi’an, China","Xi'an Electronics and Engineering Institute, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi’an Electronics and Engineering Institute, Xi’an, China","institution_ids":["https://openalex.org/I4210141776","https://openalex.org/I4210135667"]},{"raw_affiliation_string":"Xi'an Electronics and Engineering Institute, Xi'an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075013625","display_name":"Danfeng Hong","orcid":"https://orcid.org/0000-0002-3212-9584"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Danfeng Hong","raw_affiliation_strings":["German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Weßling, Germany","German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), We\u00dfling, Germany"],"affiliations":[{"raw_affiliation_string":"German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Weßling, Germany","institution_ids":["https://openalex.org/I2898391981"]},{"raw_affiliation_string":"German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), We\u00dfling, Germany","institution_ids":["https://openalex.org/I2898391981"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jocelyn Chanussot","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5039966032"],"corresponding_institution_ids":["https://openalex.org/I36234482"],"apc_list":null,"apc_paid":null,"fwci":25.1618,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.99019969,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"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":0.9994000196456909,"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":0.9994000196456909,"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":0.9970999956130981,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.989300012588501,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.753429651260376},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7530031204223633},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7312512397766113},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.726341962814331},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5522310137748718},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5517662167549133},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5204311013221741},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4632137715816498},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.44435590505599976},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4254884421825409},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4069759249687195},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.29491233825683594},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2623034119606018}],"concepts":[{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.753429651260376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7530031204223633},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7312512397766113},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.726341962814331},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5522310137748718},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5517662167549133},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5204311013221741},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4632137715816498},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.44435590505599976},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4254884421825409},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4069759249687195},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.29491233825683594},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2623034119606018},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lgrs.2020.3034700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2020.3034700","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"},{"id":"pmh:oai:elib.dlr.de:138283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/LGRS.2020.3034700>.","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7300000190734863,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G5080702389","display_name":null,"funder_award_id":"61806162","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321048","display_name":"AXA Research Fund","ror":"https://ror.org/02zxqxw53"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1932847118","https://openalex.org/W2048578702","https://openalex.org/W2130762895","https://openalex.org/W2138507544","https://openalex.org/W2169282664","https://openalex.org/W2248623186","https://openalex.org/W2559324447","https://openalex.org/W2595144186","https://openalex.org/W2611452721","https://openalex.org/W2754361766","https://openalex.org/W2755992512","https://openalex.org/W2771450566","https://openalex.org/W2793189836","https://openalex.org/W2897760800","https://openalex.org/W2902746003","https://openalex.org/W2907147407","https://openalex.org/W2910655660","https://openalex.org/W2954861366","https://openalex.org/W2965344373","https://openalex.org/W2983707810","https://openalex.org/W2994639710","https://openalex.org/W3033361357","https://openalex.org/W3036200672","https://openalex.org/W3046027728","https://openalex.org/W3047443805","https://openalex.org/W3048631361","https://openalex.org/W3101012758","https://openalex.org/W3102692100","https://openalex.org/W3103695279","https://openalex.org/W3104313739","https://openalex.org/W3104795559","https://openalex.org/W3105021316","https://openalex.org/W3105298104","https://openalex.org/W3105698493","https://openalex.org/W3122774149"],"related_works":["https://openalex.org/W2124189704","https://openalex.org/W4233585817","https://openalex.org/W2761785940","https://openalex.org/W2016045932","https://openalex.org/W1675950995","https://openalex.org/W2129933262","https://openalex.org/W2188882668","https://openalex.org/W2088323302","https://openalex.org/W2004379491","https://openalex.org/W2021544484"],"abstract_inverted_index":{"Polarimetric":[0],"synthetic":[1],"aperture":[2],"radar":[3],"(PolSAR)":[4],"image":[5,59],"classification":[6,60,103,137,163],"has":[7],"been":[8],"investigated":[9],"vigorously":[10],"in":[11,28,33],"various":[12],"remote":[13],"sensing":[14],"applications.":[15],"However,":[16],"it":[17],"is":[18,105,123,131],"still":[19],"a":[20,56,102,109],"challenging":[21],"task":[22],"nowadays.":[23],"One":[24],"significant":[25],"barrier":[26],"lies":[27],"the":[29,34,41,44,49,76,84,117,127,136,158],"speckle":[30,64],"effect":[31],"embedded":[32],"PolSAR":[35,58,151],"imaging":[36],"process,":[37],"which":[38],"greatly":[39],"degrades":[40],"quality":[42],"of":[43,86],"images":[45],"and":[46,71,97,126,165],"further":[47],"complicates":[48],"classification.":[50],"To":[51],"this":[52],"end,":[53],"we":[54,82,134],"present":[55],"novel":[57],"method":[61,160],"that":[62,157],"removes":[63],"noise":[65],"via":[66,75],"low-rank":[67],"(LR)":[68],"feature":[69],"extraction":[70],"enforces":[72],"smoothness":[73],"priors":[74],"Markov":[77],"random":[78],"field":[79],"(MRF).":[80],"Especially,":[81],"employ":[83],"mixture":[85],"Gaussian-based":[87],"robust":[88],"LR":[89],"matrix":[90],"factorization":[91],"to":[92,141],"simultaneously":[93],"extract":[94],"discriminative":[95],"features":[96],"remove":[98],"complex":[99],"noises.":[100],"Then,":[101],"map":[104,138],"obtained":[106],"by":[107,139],"applying":[108],"convolutional":[110],"neural":[111],"network":[112],"with":[113],"data":[114,152],"augmentation":[115],"on":[116,148],"extracted":[118],"features,":[119],"where":[120],"local":[121],"consistency":[122],"implicitly":[124],"involved,":[125],"insufficient":[128],"label":[129],"issue":[130],"alleviated.":[132],"Finally,":[133],"refine":[135],"MRF":[140],"enforce":[142],"contextual":[143],"smoothness.":[144],"We":[145],"conduct":[146],"experiments":[147],"two":[149],"benchmark":[150],"sets.":[153],"Experimental":[154],"results":[155],"indicate":[156],"proposed":[159],"achieves":[161],"promising":[162],"performance":[164],"preferable":[166],"spatial":[167],"consistency.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}