{"id":"https://openalex.org/W2548225538","doi":"https://doi.org/10.1109/whispers.2012.6874339","title":"Hyperspectral classification using spectral magnitude and gradient","display_name":"Hyperspectral classification using spectral magnitude and gradient","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2548225538","doi":"https://doi.org/10.1109/whispers.2012.6874339","mag":"2548225538"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2012.6874339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2012.6874339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 4th Workshop on Hyperspectral Image and Signal Processing (WHISPERS)","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/A5085403624","display_name":"Xiya Zhang","orcid":"https://orcid.org/0000-0002-0996-9710"},"institutions":[{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiya Zhang","raw_affiliation_strings":["Institute of Remote Sensing and GIS, Peking University, Beijing, P R China"],"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and GIS, Peking University, Beijing, P R China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067232074","display_name":"Haiqing Xu","orcid":"https://orcid.org/0000-0003-2084-3278"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiqing Xu","raw_affiliation_strings":["Institute of Remote Sensing and GIS, Peking University, Beijing, P R China"],"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and GIS, Peking University, Beijing, P R China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100742536","display_name":"Peijun Li","orcid":"https://orcid.org/0000-0002-4989-9892"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peijun Li","raw_affiliation_strings":["Institute of Remote Sensing and GIS, Peking University, Beijing, P R China"],"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and GIS, Peking University, Beijing, P R China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5085403624"],"corresponding_institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210166112"],"apc_list":null,"apc_paid":null,"fwci":0.5101,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75681526,"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":0.9997000098228455,"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":0.9997000098228455,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9757000207901001,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9317439794540405},{"id":"https://openalex.org/keywords/magnitude","display_name":"Magnitude (astronomy)","score":0.7394143342971802},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.665919303894043},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5777015089988708},{"id":"https://openalex.org/keywords/spectral-bands","display_name":"Spectral bands","score":0.5552993416786194},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5490975975990295},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5146976113319397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.510417640209198},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4684845209121704},{"id":"https://openalex.org/keywords/stellar-classification","display_name":"Stellar classification","score":0.4343884289264679},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.416128009557724},{"id":"https://openalex.org/keywords/spectral-shape-analysis","display_name":"Spectral shape analysis","score":0.4142674207687378},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.358257919549942},{"id":"https://openalex.org/keywords/spectral-line","display_name":"Spectral line","score":0.33106356859207153},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.22937887907028198},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.18645501136779785},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18422210216522217},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1817423701286316}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9317439794540405},{"id":"https://openalex.org/C126691448","wikidata":"https://www.wikidata.org/wiki/Q2028919","display_name":"Magnitude (astronomy)","level":2,"score":0.7394143342971802},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.665919303894043},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5777015089988708},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.5552993416786194},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5490975975990295},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5146976113319397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.510417640209198},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4684845209121704},{"id":"https://openalex.org/C180690934","wikidata":"https://www.wikidata.org/wiki/Q25377588","display_name":"Stellar classification","level":3,"score":0.4343884289264679},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.416128009557724},{"id":"https://openalex.org/C152822103","wikidata":"https://www.wikidata.org/wiki/Q7575207","display_name":"Spectral shape analysis","level":3,"score":0.4142674207687378},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.358257919549942},{"id":"https://openalex.org/C4839761","wikidata":"https://www.wikidata.org/wiki/Q212111","display_name":"Spectral line","level":2,"score":0.33106356859207153},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.22937887907028198},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.18645501136779785},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18422210216522217},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1817423701286316},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C150846664","wikidata":"https://www.wikidata.org/wiki/Q7602306","display_name":"Stars","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2012.6874339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2012.6874339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 4th Workshop on Hyperspectral Image and Signal Processing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2010319424","https://openalex.org/W2078296814","https://openalex.org/W2098057602","https://openalex.org/W2107552587","https://openalex.org/W2132870739","https://openalex.org/W2147280166"],"related_works":["https://openalex.org/W4214939362","https://openalex.org/W2050790932","https://openalex.org/W2949834766","https://openalex.org/W2024377932","https://openalex.org/W2901044172","https://openalex.org/W2582579192","https://openalex.org/W1978077614","https://openalex.org/W2361610245","https://openalex.org/W2077024826","https://openalex.org/W2371402057"],"abstract_inverted_index":{"The":[0,35,62],"spectral":[1,14,20,25,30,38,49,69,82],"variations":[2],"caused":[3],"by":[4],"geometry":[5],"and":[6,53,71,86],"incident":[7],"illumination":[8],"may":[9],"influence":[10],"classification":[11,46,76],"accuracy":[12],"using":[13,80],"information":[15],"alone.":[16],"In":[17],"this":[18],"paper,":[19],"gradient":[21,39,72],"derived":[22],"from":[23],"original":[24],"data":[26,31,84],"was":[27,43],"combined":[28],"with":[29],"for":[32,92],"improved":[33],"classification.":[34,94],"performance":[36],"of":[37,68],"in":[40,73],"lithologic":[41],"mapping":[42],"evaluated.":[44],"Two":[45],"methods,":[47],"i.e.":[48],"angle":[50],"mapper":[51],"(SAM)":[52],"extended":[54],"one-class":[55],"support":[56],"vector":[57],"machine":[58],"(OCSVM)":[59],"were":[60],"used.":[61],"results":[63,79],"showed":[64],"that":[65],"joint":[66],"use":[67],"magnitude":[70,83],"hyperspectral":[74,93],"image":[75],"outperformed":[77],"the":[78,81],"alone,":[85],"thus":[87],"is":[88],"an":[89],"effective":[90],"method":[91]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}