{"id":"https://openalex.org/W3181896199","doi":"https://doi.org/10.1109/tgrs.2021.3091860","title":"Curvature Filters-Based Multiscale Feature Extraction for Hyperspectral Image Classification","display_name":"Curvature Filters-Based Multiscale Feature Extraction for Hyperspectral Image Classification","publication_year":2021,"publication_date":"2021-07-05","ids":{"openalex":"https://openalex.org/W3181896199","doi":"https://doi.org/10.1109/tgrs.2021.3091860","mag":"3181896199"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2021.3091860","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3091860","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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/A5024679777","display_name":"Qiaobo Hao","orcid":"https://orcid.org/0000-0002-0177-7263"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiaobo Hao","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China","Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0177-7263","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]},{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100641761","display_name":"Bin Sun","orcid":"https://orcid.org/0000-0002-7029-8784"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Sun","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China","Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-7029-8784","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]},{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067097659","display_name":"Shutao Li","orcid":"https://orcid.org/0000-0002-0585-9848"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shutao Li","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China","Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0585-9848","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]},{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002083374","display_name":"Melba M. Crawford","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Melba M. Crawford","raw_affiliation_strings":["School of Civil Engineering and Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA"],"raw_orcid":"https://orcid.org/0000-0003-3459-2094","affiliations":[{"raw_affiliation_string":"School of Civil Engineering and Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057514965","display_name":"Xudong Kang","orcid":"https://orcid.org/0000-0002-3807-2531"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xudong Kang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China","Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-3807-2531","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]},{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8687,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.86885146,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"16"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9905999898910522,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9595000147819519,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7270259857177734},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6957124471664429},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6646922826766968},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6614531874656677},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5993871092796326},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5003547668457031},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4729043245315552},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.45225241780281067},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.43362846970558167},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.3838174343109131},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33216676115989685},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2411925196647644}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7270259857177734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6957124471664429},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6646922826766968},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6614531874656677},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5993871092796326},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5003547668457031},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4729043245315552},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.45225241780281067},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.43362846970558167},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.3838174343109131},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33216676115989685},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2411925196647644},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2021.3091860","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3091860","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7200000286102295,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2027762821","display_name":null,"funder_award_id":"61890962","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2347620635","display_name":null,"funder_award_id":"61801178","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4878062729","display_name":"\u9ad8\u5149\u8c31\u9065\u611f\u56fe\u50cf\u5206\u7c7b\u8bad\u7ec3\u6837\u672c\u95ee\u9898\u7814\u7a76","funder_award_id":"61871179","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6360111667","display_name":null,"funder_award_id":"2017TJ-Q09","funder_id":"https://openalex.org/F4320331108","funder_display_name":"Hunan Association for Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320331108","display_name":"Hunan Association for Science and Technology","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W236225355","https://openalex.org/W1508404128","https://openalex.org/W1535602073","https://openalex.org/W1680189815","https://openalex.org/W1938929646","https://openalex.org/W1939429412","https://openalex.org/W1973771202","https://openalex.org/W1979730959","https://openalex.org/W1994938019","https://openalex.org/W2003060733","https://openalex.org/W2018482939","https://openalex.org/W2022686119","https://openalex.org/W2057513844","https://openalex.org/W2067788981","https://openalex.org/W2095975892","https://openalex.org/W2103094532","https://openalex.org/W2104125540","https://openalex.org/W2118246710","https://openalex.org/W2119531662","https://openalex.org/W2121947440","https://openalex.org/W2135431554","https://openalex.org/W2136251662","https://openalex.org/W2136539266","https://openalex.org/W2144151128","https://openalex.org/W2152057649","https://openalex.org/W2153635508","https://openalex.org/W2164769329","https://openalex.org/W2166923144","https://openalex.org/W2290942691","https://openalex.org/W2293105860","https://openalex.org/W2496621835","https://openalex.org/W2580772840","https://openalex.org/W2624340958","https://openalex.org/W2793607189","https://openalex.org/W2793645503","https://openalex.org/W2809635958","https://openalex.org/W2890945279","https://openalex.org/W2936266191","https://openalex.org/W2947058136","https://openalex.org/W2948256530","https://openalex.org/W2977355106","https://openalex.org/W2981959903","https://openalex.org/W2994639710","https://openalex.org/W2996636458","https://openalex.org/W2998374016","https://openalex.org/W2999789528","https://openalex.org/W3046027728","https://openalex.org/W3047443805","https://openalex.org/W3100714546","https://openalex.org/W3103695279","https://openalex.org/W3105298104","https://openalex.org/W3122774149","https://openalex.org/W6609242596"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W2070598848","https://openalex.org/W4313014865","https://openalex.org/W2797752778"],"abstract_inverted_index":{"Exploring":[0],"fast":[1],"and":[2,39,114,143,151,169,223],"effective":[3],"spectral-spatial":[4,74,105,181],"feature":[5,82,221],"extraction":[6,83,222],"algorithms":[7],"for":[8,63,183,232],"hyperspectral":[9,22,201],"image":[10,123,141],"(HSI)":[11],"classification":[12,65,184,214,224],"is":[13,33,90,95,133,148,234],"one":[14],"of":[15,28,44,47,76,97,139,190,230],"the":[16,26,72,98,136,140,156,163,170,178,188,191,207,213,228],"most":[17],"focus":[18],"problems":[19],"in":[20,31,36,66],"current":[21],"remote-sensing":[23],"research.":[24],"Generally,":[25],"size":[27],"homogeneous":[29],"regions":[30],"HSIs":[32],"not":[34],"consistent":[35],"real":[37,40,200],"scenario":[38,41],"usually":[42],"consist":[43],"ground":[45],"objects":[46],"different":[48,61],"scales.":[49],"Multiscale":[50],"strategy":[51,132],"starts":[52],"to":[53,56,154,176,217],"be":[54,119],"used":[55],"construct":[57],"discriminative":[58],"features":[59,75,106,160,167,182],"at":[60],"scales":[62],"HSI":[64,220],"recent":[67],"years.":[68],"To":[69,186],"efficiently":[70,108],"characterize":[71],"multiscale":[73,81,86,104,129,158,165,180],"HSIs,":[77],"a":[78,128,144],"curvature":[79,112,166],"filters-based":[80],"method":[84,209],"with":[85],"superpixel":[87,130,171],"segmentation":[88,131],"constraint":[89],"proposed.":[91],"The":[92],"proposed":[93,192,208],"algorithm":[94],"composed":[96],"following":[99],"major":[100],"stages.":[101],"First,":[102],"global":[103,164],"are":[107,174,196],"extracted":[109],"via":[110],"progressively":[111],"filtering":[113],"downsampling":[115],"operations,":[116],"which":[117],"can":[118,210],"regarded":[120],"as":[121],"an":[122],"pyramid":[124],"decomposition":[125],"method.":[126],"Next,":[127],"applied":[134,149],"on":[135,198],"first":[137],"layer":[138],"pyramid,":[142],"weighted":[145],"mean":[146],"operation":[147],"within":[150],"among":[152],"superpixels":[153],"extract":[155],"local":[157],"spatial":[159],"(LMSFs).":[161],"Finally,":[162],"(GMCFs)":[168],"segmentation-based":[172],"LMSFs":[173],"fused":[175],"form":[177],"final":[179],"purposes.":[185],"verify":[187],"capabilities":[189],"method,":[193],"comprehensive":[194],"experiments":[195],"performed":[197],"five":[199],"datasets.":[202],"Experimental":[203],"results":[204],"demonstrate":[205],"that":[206],"significantly":[211],"improve":[212],"accuracies":[215],"compared":[216],"several":[218],"standard":[219],"methods,":[225],"especially":[226],"when":[227],"number":[229],"samples":[231],"training":[233],"limited.":[235]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
