{"id":"https://openalex.org/W2030237258","doi":"https://doi.org/10.1109/igarss.2011.6049685","title":"Dynamic band selection for hyperspectral imagery","display_name":"Dynamic band selection for hyperspectral imagery","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2030237258","doi":"https://doi.org/10.1109/igarss.2011.6049685","mag":"2030237258"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2011.6049685","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2011.6049685","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5011994790","display_name":"Keng-Hao Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Keng-Hao Liu","raw_affiliation_strings":["UMBC, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UMBC, United States","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Chein-I Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chein-I Chang","raw_affiliation_strings":["UMBC, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UMBC, United States","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9995999932289124,"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":0.9995999932289124,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9768999814987183,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9739999771118164,"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/huffman-coding","display_name":"Huffman coding","score":0.8355005979537964},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6981562376022339},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6226990818977356},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5713261365890503},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5348308086395264},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49402791261672974},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4605713188648224},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4541659951210022},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35309964418411255},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3445151448249817},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34059226512908936},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.23060405254364014},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1416739821434021}],"concepts":[{"id":"https://openalex.org/C46900642","wikidata":"https://www.wikidata.org/wiki/Q2647","display_name":"Huffman coding","level":3,"score":0.8355005979537964},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6981562376022339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6226990818977356},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5713261365890503},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5348308086395264},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49402791261672974},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4605713188648224},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4541659951210022},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35309964418411255},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3445151448249817},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34059226512908936},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.23060405254364014},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1416739821434021},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2011.6049685","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2011.6049685","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.75}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W285471286","https://openalex.org/W2082612735","https://openalex.org/W2109115094","https://openalex.org/W2137205624","https://openalex.org/W2506684654","https://openalex.org/W4205778870","https://openalex.org/W4214564766","https://openalex.org/W4248253651"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W1966933208","https://openalex.org/W2351464472","https://openalex.org/W2914103308","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3163059229","https://openalex.org/W3034375524","https://openalex.org/W2132083814","https://openalex.org/W2161708016"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,27,67,76,82,95,112,141],"new":[4],"BS,":[5,143],"called":[6],"dynamic":[7],"BS":[8,15,35,136],"(DBS)":[9],"which":[10,29],"revolutionizes":[11],"the":[12,18,86,101,128,134],"commonly":[13],"used":[14,33,98],"by":[16,66,81,92,121,127],"considering":[17],"number":[19],"of":[20],"bands":[21],"to":[22,99,110,145],"be":[23,90,119,138],"selected,":[24],"p":[25],"as":[26,54,140,146],"variable":[28,123],"varies":[30],"with":[31,57],"criterion":[32],"for":[34],"and":[36,104],"different":[37],"applications.":[38],"Its":[39],"idea":[40],"is":[41,79],"derived":[42],"from":[43,115],"information":[44],"theory":[45],"where":[46],"it":[47],"assumes":[48],"that":[49,75],"signal":[50,77,87,102,113],"sources":[51,117],"are":[52],"considered":[53,139],"source":[55,78,88,103,114],"alphabets":[56],"probabilities":[58],"being":[59,97],"their":[60],"mutual":[61],"spectral":[62,68,84],"discriminatory":[63],"powers":[64],"calculated":[65],"similarity":[69],"measure.":[70],"If":[71],"we":[72],"further":[73],"assume":[74],"accommodated":[80],"particular":[83],"band,":[85],"will":[89],"encoded":[91],"1":[93],"indicating":[94],"band":[96,108],"specify":[100],"0":[105],"otherwise.":[106],"Accordingly,":[107],"dimensionality":[109],"discriminate":[111],"other":[116],"can":[118,137],"determined":[120],"its":[122],"coding":[124],"length":[125],"obtained":[126],"Huffman":[129],"coding.":[130],"With":[131],"this":[132],"interpretation":[133],"conventional":[135],"fixed-dimensionality":[142],"referred":[144],"static":[147],"BS(SBS).":[148]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}