{"id":"https://openalex.org/W2028436154","doi":"https://doi.org/10.1109/lgrs.2014.2337957","title":"A New Sparsity-Based Band Selection Method for Target Detection of Hyperspectral Image","display_name":"A New Sparsity-Based Band Selection Method for Target Detection of Hyperspectral Image","publication_year":2014,"publication_date":"2014-08-05","ids":{"openalex":"https://openalex.org/W2028436154","doi":"https://doi.org/10.1109/lgrs.2014.2337957","mag":"2028436154"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2014.2337957","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2014.2337957","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/A5101596086","display_name":"Kang Sun","orcid":"https://orcid.org/0000-0003-3514-8681"},"institutions":[{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kang Sun","raw_affiliation_strings":["Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing, China","Key Lab. of Technol. in Geo-spatial Inf. Process. & Applic. Syst., Inst. of Electron., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]},{"raw_affiliation_string":"Key Lab. of Technol. in Geo-spatial Inf. Process. & Applic. Syst., Inst. of Electron., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063545281","display_name":"Xiurui Geng","orcid":"https://orcid.org/0000-0003-0935-3753"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiurui Geng","raw_affiliation_strings":["Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing, China","Key Lab. of Technol. in Geo-spatial Inf. Process. & Applic. Syst., Inst. of Electron., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]},{"raw_affiliation_string":"Key Lab. of Technol. in Geo-spatial Inf. Process. & Applic. Syst., Inst. of Electron., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058426226","display_name":"Luyan Ji","orcid":"https://orcid.org/0000-0001-5369-4200"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luyan Ji","raw_affiliation_strings":["Centre for Earth System Science, Tsinghua University, Beijing, China","[Centre for Earth Syst. Sci., Tsinghua Univ., Beijing, China]"],"affiliations":[{"raw_affiliation_string":"Centre for Earth System Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"[Centre for Earth Syst. Sci., Tsinghua Univ., Beijing, China]","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101596086"],"corresponding_institution_ids":["https://openalex.org/I4210110458","https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":8.72597041,"has_fulltext":false,"cited_by_count":93,"citation_normalized_percentile":{"value":0.97861564,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"12","issue":"2","first_page":"329","last_page":"333"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9715999960899353,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9671000242233276,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9243118166923523},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7169089317321777},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.6830252408981323},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6187867522239685},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5648550391197205},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5183883309364319},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5148569941520691},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.47998663783073425},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4295955300331116},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.411480575799942}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9243118166923523},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7169089317321777},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.6830252408981323},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6187867522239685},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5648550391197205},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5183883309364319},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5148569941520691},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.47998663783073425},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4295955300331116},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.411480575799942},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2014.2337957","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2014.2337957","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W846821018","https://openalex.org/W1532610010","https://openalex.org/W1968589019","https://openalex.org/W1977325095","https://openalex.org/W1984568490","https://openalex.org/W1986931325","https://openalex.org/W1993369775","https://openalex.org/W1993733001","https://openalex.org/W2040648638","https://openalex.org/W2042255844","https://openalex.org/W2042844405","https://openalex.org/W2047029347","https://openalex.org/W2060542593","https://openalex.org/W2063978378","https://openalex.org/W2089372326","https://openalex.org/W2089731888","https://openalex.org/W2097961679","https://openalex.org/W2109836508","https://openalex.org/W2135046866","https://openalex.org/W2137205624","https://openalex.org/W2138038253","https://openalex.org/W2143277109","https://openalex.org/W2150566919","https://openalex.org/W2150990614","https://openalex.org/W2152734820","https://openalex.org/W2163970536","https://openalex.org/W2287804611","https://openalex.org/W4248253651","https://openalex.org/W6623562790"],"related_works":["https://openalex.org/W2132083814","https://openalex.org/W2292979300","https://openalex.org/W2137369096","https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907"],"abstract_inverted_index":{"Band":[0],"selection":[1,55,90],"(BS)":[2],"plays":[3],"an":[4],"important":[5],"role":[6],"in":[7],"the":[8,17,33,74,79,87,95,99],"dimensionality":[9],"reduction":[10],"of":[11,97],"hyperspectral":[12,106],"data.":[13],"However,":[14],"as":[15],"to":[16],"existing":[18],"BS":[19,37,45,58,76,115],"methods,":[20],"few":[21],"are":[22],"specially":[23],"designed":[24],"for":[25,47,117],"target":[26,34,48,118],"detection.":[27,119],"In":[28],"this":[29],"letter,":[30],"we":[31],"combine":[32],"detection":[35],"and":[36,40,54],"process":[38,91],"together":[39],"put":[41],"forward":[42],"a":[43,63,112],"new":[44],"method":[46,116],"detection,":[49],"named":[50],"least":[51],"absolute":[52],"shrinkage":[53],"operator":[56],"(LASSO)-based":[57],"(LBS).":[59],"Interestingly,":[60],"by":[61],"using":[62],"linear":[64],"regression":[65],"model":[66],"with":[67],"L1":[68],"regularization":[69],"(LASSO":[70],"model),":[71],"LBS":[72,110],"transforms":[73],"discrete":[75],"problem":[77],"into":[78],"continuous":[80],"optimization":[81],"problem,":[82],"which":[83],"cannot":[84],"only":[85],"avoid":[86],"complicated":[88],"subset":[89],"but":[92],"also":[93],"evaluate":[94],"importance":[96],"all":[98],"bands":[100],"simultaneously.":[101],"The":[102],"experiments":[103],"on":[104],"real":[105],"data":[107],"demonstrate":[108],"that":[109],"is":[111],"very":[113],"effective":[114]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
