{"id":"https://openalex.org/W2116223915","doi":"https://doi.org/10.1109/igarss.2011.6049727","title":"Bayesian fusion of hyperspectral and multispectral images using Gaussian scale mixture prior","display_name":"Bayesian fusion of hyperspectral and multispectral images using Gaussian scale mixture prior","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2116223915","doi":"https://doi.org/10.1109/igarss.2011.6049727","mag":"2116223915"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2011.6049727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2011.6049727","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":"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/A5100376972","display_name":"Yifan Zhang","orcid":"https://orcid.org/0000-0003-4533-3880"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yifan Zhang","raw_affiliation_strings":["School of Electronics and Information, Shaanxi Key Laboratory of Information Acquisition and Processing, Northwestern Polytechnical University, Xian, China","School of Electronics and Information,Northwestern Polytechnical University,Shaanxi Key Laboratory of Information Acquisition and Processing,Xi'an 710129,China)"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Shaanxi Key Laboratory of Information Acquisition and Processing, Northwestern Polytechnical University, Xian, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Electronics and Information,Northwestern Polytechnical University,Shaanxi Key Laboratory of Information Acquisition and Processing,Xi'an 710129,China)","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067207818","display_name":"Shaohui Mei","orcid":"https://orcid.org/0000-0002-8018-596X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohui Mei","raw_affiliation_strings":["School of Electronics and Information, Shaanxi Key Laboratory of Information Acquisition and Processing, Northwestern Polytechnical University, Xian, China","School of Electronics and Information,Northwestern Polytechnical University,Shaanxi Key Laboratory of Information Acquisition and Processing,Xi'an 710129,China)"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Shaanxi Key Laboratory of Information Acquisition and Processing, Northwestern Polytechnical University, Xian, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Electronics and Information,Northwestern Polytechnical University,Shaanxi Key Laboratory of Information Acquisition and Processing,Xi'an 710129,China)","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086729425","display_name":"Mingyi He","orcid":"https://orcid.org/0000-0003-2051-6955"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyi He","raw_affiliation_strings":["School of Electronics and Information, Shaanxi Key Laboratory of Information Acquisition and Processing, Northwestern Polytechnical University, Xian, China","School of Electronics and Information,Northwestern Polytechnical University,Shaanxi Key Laboratory of Information Acquisition and Processing,Xi'an 710129,China)"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Shaanxi Key Laboratory of Information Acquisition and Processing, Northwestern Polytechnical University, Xian, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Electronics and Information,Northwestern Polytechnical University,Shaanxi Key Laboratory of Information Acquisition and Processing,Xi'an 710129,China)","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100376972"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.19223965,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"4383","issue":null,"first_page":"2531","last_page":"2534"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994000196456909,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991000294685364,"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":0.8015342950820923},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6621370911598206},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.6366330981254578},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6047459244728088},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5943388342857361},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5936071872711182},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.592200756072998},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5088965892791748},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.48401138186454773},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.48103243112564087},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4799909293651581},{"id":"https://openalex.org/keywords/gaussian-network-model","display_name":"Gaussian network model","score":0.4751063287258148},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.4620620012283325},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4336165189743042},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4327854812145233},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3537423014640808},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33091026544570923}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8015342950820923},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6621370911598206},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.6366330981254578},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6047459244728088},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5943388342857361},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5936071872711182},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.592200756072998},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5088965892791748},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.48401138186454773},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.48103243112564087},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4799909293651581},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.4751063287258148},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4620620012283325},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4336165189743042},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4327854812145233},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3537423014640808},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33091026544570923},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/igarss.2011.6049727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2011.6049727","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2012807998","https://openalex.org/W2075621901","https://openalex.org/W2078125016","https://openalex.org/W2100056645","https://openalex.org/W2113945798","https://openalex.org/W2117146861","https://openalex.org/W2131345279","https://openalex.org/W2144948131","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2906564031","https://openalex.org/W1992295166","https://openalex.org/W2350507978","https://openalex.org/W2143508933","https://openalex.org/W2016260880","https://openalex.org/W3162483426","https://openalex.org/W2388204628","https://openalex.org/W2194875745","https://openalex.org/W2386749094","https://openalex.org/W2055782493"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,12,22,36,74,118],"wavelet-based":[4],"Bayesian":[5],"fusion":[6,95],"framework":[7],"is":[8,19,45,51,78,83],"presented,":[9],"in":[10],"which":[11,50],"low":[13],"spatial":[14,24],"resolution":[15,25],"hyperspectral":[16],"(HS)":[17],"image":[18,28,94],"fused":[20],"with":[21,114],"high":[23],"multi-spectral":[26],"(MS)":[27],"by":[29,85],"accounting":[30],"for":[31,88,121],"the":[32,48,58,71,99,108],"joint":[33],"statistics.":[34],"Particularly,":[35],"zero-mean":[37],"heavy-tailed":[38],"model,":[39,44],"Gaussian":[40,67,119],"Scale":[41],"Mixture":[42],"(GSM)":[43],"employed":[46],"as":[47,96,98],"prior,":[49],"believed":[52],"to":[53],"be":[54],"capable":[55],"of":[56,60,102,107],"modelling":[57],"distribution":[59],"wavelet":[61],"coefficients":[62],"more":[63],"accurately":[64],"than":[65],"traditional":[66],"model.":[68],"To":[69],"keep":[70],"calculations":[72],"feasible,":[73],"practical":[75],"implementation":[76],"scheme":[77],"presented.":[79],"The":[80,104],"proposed":[81,109],"approach":[82,110],"validated":[84],"simulation":[86],"experiments":[87],"both":[89],"general":[90],"HS":[91],"and":[92],"MS":[93],"well":[97],"specific":[100],"case":[101],"pansharpening.":[103],"experimental":[105],"results":[106],"are":[111],"also":[112],"compared":[113],"its":[115],"counterpart":[116],"employing":[117],"prior":[120],"performance":[122],"evaluation.":[123]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
