{"id":"https://openalex.org/W2901504063","doi":"https://doi.org/10.1109/igarss.2018.8518351","title":"Gabor Wavelet Based Feature Extraction and Fusion for Hyperspectral and Lidar Remote Sensing Data","display_name":"Gabor Wavelet Based Feature Extraction and Fusion for Hyperspectral and Lidar Remote Sensing Data","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2901504063","doi":"https://doi.org/10.1109/igarss.2018.8518351","mag":"2901504063"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8518351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","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/A5035753061","display_name":"Sen Jia","orcid":"https://orcid.org/0000-0001-9742-5037"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sen Jia","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100691593","display_name":"Meng Zhang","orcid":"https://orcid.org/0000-0003-1465-9714"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Zhang","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051616840","display_name":"Jiasong Zhu","orcid":"https://orcid.org/0000-0001-6177-3363"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiasong Zhu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035753061"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.2057,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.59989534,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9976000189781189,"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":0.9937999844551086,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8515052795410156},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7075371146202087},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.6754215955734253},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6609393954277039},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.622017502784729},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5930402278900146},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5764052867889404},{"id":"https://openalex.org/keywords/gabor-wavelet","display_name":"Gabor wavelet","score":0.5685168504714966},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.543343186378479},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5232057571411133},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.49642711877822876},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47921091318130493},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46241283416748047},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4536662697792053},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.32061147689819336},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.19522219896316528},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.163301020860672},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15199041366577148}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8515052795410156},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7075371146202087},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.6754215955734253},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6609393954277039},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.622017502784729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5930402278900146},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5764052867889404},{"id":"https://openalex.org/C136902061","wikidata":"https://www.wikidata.org/wiki/Q16981559","display_name":"Gabor wavelet","level":5,"score":0.5685168504714966},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.543343186378479},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5232057571411133},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.49642711877822876},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47921091318130493},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46241283416748047},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4536662697792053},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.32061147689819336},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.19522219896316528},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.163301020860672},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15199041366577148},{"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":1,"locations":[{"id":"doi:10.1109/igarss.2018.8518351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1497089125","https://openalex.org/W1965228281","https://openalex.org/W1965309615","https://openalex.org/W1979743748","https://openalex.org/W2012010354","https://openalex.org/W2031802401","https://openalex.org/W2096634748","https://openalex.org/W2113526566","https://openalex.org/W2124547294","https://openalex.org/W2138583748","https://openalex.org/W2144966944","https://openalex.org/W2153635508","https://openalex.org/W2342652911","https://openalex.org/W3120421331","https://openalex.org/W6681546829"],"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/W2070598848","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440","https://openalex.org/W2343470940"],"abstract_inverted_index":{"In":[0,82],"recent":[1],"years,":[2],"it":[3],"has":[4,42],"been":[5,43],"found":[6],"that":[7],"the":[8,26,78,103,113,136,189,196],"fusion":[9,92,101,115],"processing":[10],"of":[11,29,47,102,112,123,200],"remote":[12,50,164],"sensing":[13,51,165],"data":[14,39,57,76,122,193],"produced":[15],"by":[16,149],"multiple":[17],"sensors":[18],"is":[19,72,117],"often":[20],"effective":[21],"for":[22,40,160,203],"material":[23],"classification.":[24,204],"Specifically,":[25],"joint":[27,179],"use":[28],"hyperspectral":[30,54,171,191],"image":[31,192],"(HSI)":[32],"and":[33,55,63,69,91,106,120,144,181],"Light":[34],"Detection":[35],"And":[36],"Ranging":[37],"(LiDAR)":[38],"classification":[41,162],"an":[44,87],"active":[45],"topic":[46],"research":[48],"in":[49,77,163],"field.":[52],"Since":[53],"LiDAR":[56,124],"provide":[58],"complementary":[59],"information":[60,79,183],"(spectral":[61],"reflectance,":[62],"vertical":[64],"structure,":[65,140],"respectively),":[66],"one":[67],"promising":[68],"challenging":[70],"approach":[71,116,202],"to":[73,99,128,154,174,177],"fuse":[74],"these":[75],"extraction":[80,90],"procedure.":[81],"this":[83],"paper,":[84],"we":[85],"propose":[86],"efficient":[88],"feature":[89,138],"method":[93],"based":[94,134],"on":[95,135,188],"Gabor":[96,137,150],"wavelet,":[97],"leading":[98],"a":[100],"spectral,":[104],"spatial":[105,180],"elevation":[107,119],"data.":[108],"The":[109,146],"core":[110],"idea":[111],"proposed":[114],"stacking":[118],"intensity":[121],"as":[125],"additional":[126],"channels":[127],"spectral":[129],"bands.":[130],"Our":[131],"strategies":[132],"are":[133,142],"stack":[139],"which":[141],"natural":[143],"effective.":[145],"features":[147,157],"extracted":[148],"wavelets":[151],"have":[152,194],"proved":[153],"be":[155],"discriminant":[156],"when":[158,168],"considered":[159],"thematic":[161],"applications":[166],"especially":[167],"dealing":[169],"with":[170],"images":[172],"due":[173],"their":[175],"ability":[176],"extract":[178],"spectrum":[182],"from":[184],"HSI.":[185],"Experimental":[186],"results":[187],"real":[190],"shown":[195],"better":[197],"discriminative":[198],"power":[199],"our":[201]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}