{"id":"https://openalex.org/W2296176673","doi":"https://doi.org/10.1109/icip.2015.7351124","title":"A spectral unmixing method based on wavelet weighted similarity","display_name":"A spectral unmixing method based on wavelet weighted similarity","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2296176673","doi":"https://doi.org/10.1109/icip.2015.7351124","mag":"2296176673"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2015.7351124","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351124","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","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/A5089486724","display_name":"Qingyu Pang","orcid":null},"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":"Qingyu Pang","raw_affiliation_strings":["Tsinghua University, Beijing, Beijing, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101579038","display_name":"Jing Yu","orcid":"https://orcid.org/0000-0002-2854-8620"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Yu","raw_affiliation_strings":["College of Computer Science and Technology, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024318974","display_name":"Weidong Sun","orcid":"https://orcid.org/0000-0002-8931-8407"},"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":"Weidong Sun","raw_affiliation_strings":["Tsinghua University, Beijing, Beijing, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1865","last_page":"1869"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9983999729156494,"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":0.9937999844551086,"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/endmember","display_name":"Endmember","score":0.8999122381210327},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.861762523651123},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7891061305999756},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7332610487937927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7028990387916565},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6755077242851257},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5566728115081787},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.5538408756256104},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.507398784160614},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4865359365940094},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4783689081668854},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.45004284381866455},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.42801812291145325},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.4116579592227936},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30154862999916077},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.2523854970932007},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1041422188282013},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.053378552198410034}],"concepts":[{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.8999122381210327},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.861762523651123},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7891061305999756},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7332610487937927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7028990387916565},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6755077242851257},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5566728115081787},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.5538408756256104},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.507398784160614},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4865359365940094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4783689081668854},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.45004284381866455},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.42801812291145325},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.4116579592227936},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30154862999916077},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.2523854970932007},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1041422188282013},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.053378552198410034},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2015.7351124","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351124","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W228380312","https://openalex.org/W846821018","https://openalex.org/W1608180792","https://openalex.org/W1992367803","https://openalex.org/W2067782748","https://openalex.org/W2069231830","https://openalex.org/W2069624343","https://openalex.org/W2096673829","https://openalex.org/W2107120407","https://openalex.org/W2143500192","https://openalex.org/W2506684654","https://openalex.org/W3020861184","https://openalex.org/W4233760599","https://openalex.org/W6623562790","https://openalex.org/W6675750237"],"related_works":["https://openalex.org/W2089298795","https://openalex.org/W2773002387","https://openalex.org/W1980988957","https://openalex.org/W2802800261","https://openalex.org/W2766484909","https://openalex.org/W2163867257","https://openalex.org/W1992367803","https://openalex.org/W2059578032","https://openalex.org/W2811256493","https://openalex.org/W2898368675"],"abstract_inverted_index":{"With":[0],"the":[1,5,23,26,31,40,55,69,77,83],"rapid":[2],"development":[3],"of":[4,35,88,98],"hyperspectral":[6,81],"technology,":[7],"spectra":[8,29,34],"unmixing":[9,65,101],"has":[10,91],"received":[11],"more":[12,14],"and":[13,30,38,85,94],"attentions.":[15],"In":[16],"this":[17],"paper,":[18],"in":[19],"order":[20],"to":[21],"measure":[22],"similarity":[24,47,72],"between":[25],"extracted":[27],"endmember":[28],"actual":[32],"corresponding":[33],"land":[36],"covers":[37],"maintain":[39],"spectral":[41,64,100],"absorption":[42],"feature,":[43],"a":[44,63],"wavelet":[45,70],"weighted":[46,71],"is":[48,73],"presented.":[49],"And":[50],"by":[51],"introducing":[52],"it":[53],"into":[54],"minimum":[56],"distance":[57],"constrained":[58],"nonnegative":[59],"matrix":[60],"factorization":[61],"method,":[62],"method":[66,90],"based":[67],"on":[68,76],"proposed.":[74],"Base":[75],"experiments":[78],"with":[79,96],"real":[80,86],"image,":[82],"feasibility":[84],"performance":[87],"our":[89],"been":[92],"examined":[93],"compared":[95],"that":[97],"unsupervised":[99],"method.":[102]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
