{"id":"https://openalex.org/W3005018372","doi":"https://doi.org/10.1109/lgrs.2020.2968171","title":"Pan-Sharpening Based on Background Prior Saliency and Joint Sparse Detail Extraction","display_name":"Pan-Sharpening Based on Background Prior Saliency and Joint Sparse Detail Extraction","publication_year":2020,"publication_date":"2020-02-06","ids":{"openalex":"https://openalex.org/W3005018372","doi":"https://doi.org/10.1109/lgrs.2020.2968171","mag":"3005018372"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2020.2968171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2020.2968171","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/A5087779583","display_name":"Libao Zhang","orcid":"https://orcid.org/0000-0002-0888-2330"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Libao Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Beijing Normal University, Beijing, China","[School of Artificial Intelligence, Beijing Normal University, Beijing, China.]"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"[School of Artificial Intelligence, Beijing Normal University, Beijing, China.]","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100714899","display_name":"Yang Sun","orcid":"https://orcid.org/0000-0001-6265-1309"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Sun","raw_affiliation_strings":["School of Artificial Intelligence, Beijing Normal University, Beijing, China","[School of Artificial Intelligence, Beijing Normal University, Beijing, China.]"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"[School of Artificial Intelligence, Beijing Normal University, Beijing, China.]","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5087779583"],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":null,"apc_paid":null,"fwci":0.1887,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.54464701,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"18","issue":"1","first_page":"142","last_page":"146"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9987000226974487,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9984999895095825,"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/sharpening","display_name":"Sharpening","score":0.8600056171417236},{"id":"https://openalex.org/keywords/panchromatic-film","display_name":"Panchromatic film","score":0.7999650835990906},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7695221900939941},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.7402772307395935},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7036614418029785},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5943892002105713},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5926592350006104},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5256824493408203},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5169731974601746},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5165128111839294},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.513393759727478},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42551174759864807},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4199903607368469},{"id":"https://openalex.org/keywords/spatial-filter","display_name":"Spatial filter","score":0.4144509434700012},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2701728641986847}],"concepts":[{"id":"https://openalex.org/C2781137444","wikidata":"https://www.wikidata.org/wiki/Q237105","display_name":"Sharpening","level":2,"score":0.8600056171417236},{"id":"https://openalex.org/C107445234","wikidata":"https://www.wikidata.org/wiki/Q280995","display_name":"Panchromatic film","level":3,"score":0.7999650835990906},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7695221900939941},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7402772307395935},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7036614418029785},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5943892002105713},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5926592350006104},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5256824493408203},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5169731974601746},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5165128111839294},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.513393759727478},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42551174759864807},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4199903607368469},{"id":"https://openalex.org/C121475858","wikidata":"https://www.wikidata.org/wiki/Q2735911","display_name":"Spatial filter","level":2,"score":0.4144509434700012},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2701728641986847},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2020.2968171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2020.2968171","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":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4399999976158142}],"awards":[{"id":"https://openalex.org/G3872703625","display_name":null,"funder_award_id":"41771407","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4503850585","display_name":null,"funder_award_id":"L182029","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G5547827018","display_name":null,"funder_award_id":"61571050","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2003068273","https://openalex.org/W2020679958","https://openalex.org/W2022075948","https://openalex.org/W2064366277","https://openalex.org/W2088538848","https://openalex.org/W2118246710","https://openalex.org/W2125188192","https://openalex.org/W2149720806","https://openalex.org/W2151693816","https://openalex.org/W2154789478","https://openalex.org/W2160547390","https://openalex.org/W2163677711","https://openalex.org/W2339428543","https://openalex.org/W2528170672","https://openalex.org/W2560449954","https://openalex.org/W2755649753","https://openalex.org/W2770525455","https://openalex.org/W2901912387"],"related_works":["https://openalex.org/W4254327447","https://openalex.org/W2033186943","https://openalex.org/W2816335205","https://openalex.org/W2158371478","https://openalex.org/W2158027388","https://openalex.org/W2182807969","https://openalex.org/W2084382156","https://openalex.org/W2019692878","https://openalex.org/W4313315820","https://openalex.org/W2158398018"],"abstract_inverted_index":{"For":[0],"remote":[1,59,68],"sensing":[2,60,69],"images,":[3],"the":[4,27,65,78,94,102,117,144,154,161,165,172,190,205,210],"spectral":[5,24,98,176,211],"and":[6,38,53,81,97,104,112,120,139,151,175,192,208],"spatial":[7,17,96,125,174,206],"quality":[8,207],"requirements":[9,100,178],"vary":[10],"across":[11],"regions.":[12],"Foreground":[13],"objects":[14],"need":[15],"high":[16,23],"quality,":[18],"while":[19],"background":[20,50,82],"regions":[21,181],"require":[22],"fidelity":[25],"for":[26,36,58,179],"successive":[28],"processing.":[29],"Saliency":[30],"analysis":[31,74],"is":[32,84,157],"an":[33],"effective":[34],"tool":[35],"distinguishing":[37],"achieving":[39],"these":[40],"requirements.":[41],"Thus,":[42],"we":[43,107],"propose":[44,108],"a":[45,72,88,109,200],"pan-sharpening":[46,166],"method":[47,75,114,169,198],"based":[48,76,115],"on":[49,77,116],"prior":[51,83],"saliency":[52,73],"joint":[54],"sparse":[55,121,145],"detail":[56,110,162],"extraction":[57,111],"images.":[61],"First,":[62],"aimed":[63],"at":[64,203],"characteristics":[66],"of":[67,101],"image":[70],"fusion,":[71],"foreground":[79,103],"distribution":[80],"proposed":[85],"to":[86,148,159,185],"produce":[87],"regulation":[89,155],"factor,":[90],"which":[91],"can":[92,170],"reflect":[93],"different":[95,180],"information":[99],"background.":[105],"Then,":[106],"fusion":[113],"guided":[118],"filter":[119],"representation.":[122],"We":[123],"extract":[124],"details":[126],"not":[127],"only":[128],"from":[129,135],"panchromatic":[130],"(PAN)":[131],"images":[132,138],"but":[133],"also":[134],"multispectral":[136],"(MS)":[137],"fuse":[140],"them":[141],"by":[142],"maximizing":[143],"coefficient":[146],"strategy":[147],"reduce":[149],"instabilities":[150],"dissimilarities.":[152],"Finally,":[153],"factor":[156],"used":[158],"regulate":[160],"injection":[163],"in":[164],"process.":[167],"Our":[168],"satisfy":[171],"various":[173],"resolution":[177],"more":[182],"accurately.":[183],"Compared":[184],"other":[186],"state-of-art":[187],"methods,":[188],"both":[189],"visual":[191],"quantitative":[193],"results":[194],"reveal":[195],"that":[196],"our":[197],"has":[199],"better":[201],"performance":[202],"improving":[204],"preserving":[209],"fidelity.":[212]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}