{"id":"https://openalex.org/W4416798012","doi":"https://doi.org/10.1109/lgrs.2025.3638414","title":"Dual-Branch ViT With Polarimetric Spatial Profile for PolSAR Image Classification","display_name":"Dual-Branch ViT With Polarimetric Spatial Profile for PolSAR Image Classification","publication_year":2025,"publication_date":"2025-11-28","ids":{"openalex":"https://openalex.org/W4416798012","doi":"https://doi.org/10.1109/lgrs.2025.3638414"},"language":null,"primary_location":{"id":"doi:10.1109/lgrs.2025.3638414","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3638414","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/A5010564666","display_name":"Nabajyoti Das","orcid":"https://orcid.org/0009-0007-5086-5343"},"institutions":[{"id":"https://openalex.org/I126601174","display_name":"Tezpur University","ror":"https://ror.org/005x56091","country_code":"IN","type":"education","lineage":["https://openalex.org/I126601174"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nabajyoti Das","raw_affiliation_strings":["Department of Computer Science and Engineering, Tezpur University, Tezpur, Assam, India"],"raw_orcid":"https://orcid.org/0009-0007-5086-5343","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Tezpur University, Tezpur, Assam, India","institution_ids":["https://openalex.org/I126601174"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035487111","display_name":"Swarnajyoti Patra","orcid":"https://orcid.org/0000-0003-4300-9307"},"institutions":[{"id":"https://openalex.org/I126601174","display_name":"Tezpur University","ror":"https://ror.org/005x56091","country_code":"IN","type":"education","lineage":["https://openalex.org/I126601174"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Swarnajyoti Patra","raw_affiliation_strings":["Department of Computer Science and Engineering, Tezpur University, Tezpur, Assam, India"],"raw_orcid":"https://orcid.org/0000-0003-4300-9307","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Tezpur University, Tezpur, Assam, India","institution_ids":["https://openalex.org/I126601174"]}]},{"author_position":"last","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":"Lorenzo Bruzzone","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Trento, Italy"],"raw_orcid":"https://orcid.org/0000-0002-6036-459X","affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.4323101,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","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":0.9772999882698059,"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":0.9772999882698059,"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":0.005499999970197678,"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/T12050","display_name":"Optical Polarization and Ellipsometry","score":0.003700000001117587,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6643999814987183},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.6190000176429749},{"id":"https://openalex.org/keywords/polarimetry","display_name":"Polarimetry","score":0.6096000075340271},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5777999758720398},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5687000155448914},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.5461000204086304},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.5037999749183655},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5012000203132629},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.4887000024318695}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6912999749183655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6819000244140625},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6643999814987183},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.6190000176429749},{"id":"https://openalex.org/C28493345","wikidata":"https://www.wikidata.org/wiki/Q899381","display_name":"Polarimetry","level":3,"score":0.6096000075340271},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5777999758720398},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5687000155448914},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.5461000204086304},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.5037999749183655},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5012000203132629},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4909000098705292},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.4887000024318695},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43810001015663147},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3686999976634979},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.36250001192092896},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.310699999332428},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2718000113964081},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.25769999623298645},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.25060001015663147},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3638414","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3638414","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1820232756","https://openalex.org/W1996061706","https://openalex.org/W2086729262","https://openalex.org/W2118246710","https://openalex.org/W2127193590","https://openalex.org/W2133989913","https://openalex.org/W2541257691","https://openalex.org/W2559324447","https://openalex.org/W2793189836","https://openalex.org/W3094502228","https://openalex.org/W4237764598","https://openalex.org/W4285274933","https://openalex.org/W4317796315","https://openalex.org/W4391547680","https://openalex.org/W4394711374","https://openalex.org/W4402742845","https://openalex.org/W4404893145","https://openalex.org/W4405769242","https://openalex.org/W4410393822"],"related_works":[],"abstract_inverted_index":{"Polarimetric":[0],"Synthetic":[1],"Aperture":[2],"Radar":[3],"(PolSAR)":[4],"image":[5,44,86],"classification":[6,45],"remains":[7],"challenging":[8],"due":[9],"to":[10,72],"complex":[11],"scattering":[12,76],"mechanisms,":[13],"speckle":[14],"noise,":[15],"and":[16,78,113,135,156],"the":[17,21,26,55,63,84,90,96,109,114,132,136,150],"difficulty":[18],"of":[19,28,57,83,154],"selecting":[20],"most":[22],"informative":[23],"features":[24,112],"from":[25],"multitude":[27],"derivable":[29],"polarimetric":[30,111],"representations.":[31],"To":[32],"address":[33],"these":[34],"challenges,":[35],"we":[36],"propose":[37],"a":[38,58,99,123],"novel":[39],"two-step":[40],"methodology":[41],"for":[42],"PolSAR":[43,85],"that":[46,105,142],"utilizes":[47],"an":[48],"advanced":[49,66],"feature":[50,67],"extraction":[51,68],"technique":[52],"while":[53,87],"leveraging":[54],"strengths":[56],"vision":[59],"transformer(ViT)":[60],"architecture.":[61],"In":[62,95],"first":[64],"step,":[65,98],"techniques":[69],"are":[70],"explored":[71],"capture":[73],"multiscale":[74],"spatial":[75,116],"information":[77,82,120],"preserve":[79],"crucial":[80],"structural":[81],"effectively":[88],"mitigating":[89],"noise":[91],"present":[92],"on":[93,131],"it.":[94],"second":[97],"dual-branch":[100],"ViT":[101],"(DB-ViT)":[102],"is":[103],"proposed":[104],"simultaneously":[106],"processes":[107],"both":[108],"original":[110],"extracted":[115],"features,":[117],"enabling":[118],"effective":[119],"fusion":[121],"through":[122],"local":[124],"window":[125],"attention":[126],"transformer":[127],"(LWAT).":[128],"Extensive":[129],"experiments":[130],"Flevoland":[133],"AIRSAR":[134],"San-Francisco":[137],"RADARSAT-2":[138],"benchmark":[139],"datasets":[140],"demonstrated":[141],"our":[143],"approach":[144],"consistently":[145],"outperforms":[146],"state-of-the-art":[147],"methods,":[148],"achieving":[149],"highest":[151],"overall":[152],"accuracies":[153],"99.50%":[155],"99.51%,":[157],"respectively.":[158]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-28T00:00:00"}
