{"id":"https://openalex.org/W2792144524","doi":"https://doi.org/10.1109/tip.2018.2814210","title":"A MAP-Based Approach for Hyperspectral Imagery Super-Resolution","display_name":"A MAP-Based Approach for Hyperspectral Imagery Super-Resolution","publication_year":2018,"publication_date":"2018-03-09","ids":{"openalex":"https://openalex.org/W2792144524","doi":"https://doi.org/10.1109/tip.2018.2814210","mag":"2792144524","pmid":"https://pubmed.ncbi.nlm.nih.gov/29994066"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2018.2814210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2814210","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hdl.handle.net/11511/35627","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008084526","display_name":"Hasan Irmak","orcid":"https://orcid.org/0000-0003-1953-3950"},"institutions":[{"id":"https://openalex.org/I56303344","display_name":"Aselsan (Turkey)","ror":"https://ror.org/04knh8e66","country_code":"TR","type":"company","lineage":["https://openalex.org/I56303344"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Hasan Irmak","raw_affiliation_strings":["Radar and Electronic Warfare Systems Business Sector (REHIS), ASELSAN Inc., Ankara, Turkey"],"affiliations":[{"raw_affiliation_string":"Radar and Electronic Warfare Systems Business Sector (REHIS), ASELSAN Inc., Ankara, Turkey","institution_ids":["https://openalex.org/I56303344"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009437653","display_name":"G\u00f6zde Bozda\u011f\u0131 Akar","orcid":"https://orcid.org/0000-0002-4227-5606"},"institutions":[{"id":"https://openalex.org/I201799495","display_name":"Middle East Technical University","ror":"https://ror.org/014weej12","country_code":"TR","type":"education","lineage":["https://openalex.org/I201799495"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Gozde Bozdagi Akar","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Middle East Techical University, Ankara, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Middle East Techical University, Ankara, Turkey","institution_ids":["https://openalex.org/I201799495"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012317612","display_name":"Seniha Esen Y\u00fcksel","orcid":"https://orcid.org/0000-0002-8868-1132"},"institutions":[{"id":"https://openalex.org/I66514158","display_name":"Hacettepe University","ror":"https://ror.org/04kwvgz42","country_code":"TR","type":"education","lineage":["https://openalex.org/I66514158"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Seniha Esen Yuksel","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Hacettepe University, Ankara, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Hacettepe University, Ankara, Turkey","institution_ids":["https://openalex.org/I66514158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008084526"],"corresponding_institution_ids":["https://openalex.org/I56303344"],"apc_list":null,"apc_paid":null,"fwci":6.2571,"has_fulltext":false,"cited_by_count":77,"citation_normalized_percentile":{"value":0.9655527,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"27","issue":"6","first_page":"2942","last_page":"2951"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","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/T11659","display_name":"Advanced Image Fusion Techniques","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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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":0.9984999895095825,"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":0.7709932327270508},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5946595072746277},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.5263582468032837},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5225031971931458},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5027647018432617},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.48480024933815},{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.42394310235977173},{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.41233670711517334},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40819913148880005},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38135769963264465},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.196977436542511},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1855485439300537},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0981631875038147}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7709932327270508},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5946595072746277},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.5263582468032837},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5225031971931458},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5027647018432617},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.48480024933815},{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.42394310235977173},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.41233670711517334},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40819913148880005},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38135769963264465},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.196977436542511},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1855485439300537},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0981631875038147},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2018.2814210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2814210","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:29994066","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29994066","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:open.metu.edu.tr:11511/35627","is_oa":true,"landing_page_url":"https://hdl.handle.net/11511/35627","pdf_url":null,"source":{"id":"https://openalex.org/S4306402495","display_name":"OpenMETU (Middle East Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I201799495","host_organization_name":"Middle East Technical University","host_organization_lineage":["https://openalex.org/I201799495"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:open.metu.edu.tr:11511/35627","is_oa":true,"landing_page_url":"https://hdl.handle.net/11511/35627","pdf_url":null,"source":{"id":"https://openalex.org/S4306402495","display_name":"OpenMETU (Middle East Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I201799495","host_organization_name":"Middle East Technical University","host_organization_lineage":["https://openalex.org/I201799495"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8799999952316284}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W123101483","https://openalex.org/W581184175","https://openalex.org/W935139217","https://openalex.org/W1878940107","https://openalex.org/W1885185971","https://openalex.org/W1916874600","https://openalex.org/W1964570608","https://openalex.org/W1976615758","https://openalex.org/W1990231296","https://openalex.org/W2012946078","https://openalex.org/W2021046129","https://openalex.org/W2040325979","https://openalex.org/W2048225904","https://openalex.org/W2070424424","https://openalex.org/W2082925067","https://openalex.org/W2085766171","https://openalex.org/W2099703033","https://openalex.org/W2100109944","https://openalex.org/W2107120407","https://openalex.org/W2120893400","https://openalex.org/W2121058967","https://openalex.org/W2122143316","https://openalex.org/W2123886106","https://openalex.org/W2127062304","https://openalex.org/W2131659181","https://openalex.org/W2133665775","https://openalex.org/W2136810081","https://openalex.org/W2137062213","https://openalex.org/W2150835169","https://openalex.org/W2162842940","https://openalex.org/W2163886442","https://openalex.org/W2165709183","https://openalex.org/W2165755981","https://openalex.org/W2194818953","https://openalex.org/W2200474412","https://openalex.org/W2221899823","https://openalex.org/W2263468737","https://openalex.org/W2327023139","https://openalex.org/W2332800080","https://openalex.org/W2418677139","https://openalex.org/W2422754456","https://openalex.org/W2494274259","https://openalex.org/W2514046700","https://openalex.org/W2520844005","https://openalex.org/W2547609874","https://openalex.org/W2547665164","https://openalex.org/W2588000623","https://openalex.org/W2622007554","https://openalex.org/W2752716059","https://openalex.org/W2765761734","https://openalex.org/W2962907479","https://openalex.org/W2963442801","https://openalex.org/W3102912004","https://openalex.org/W4205154133","https://openalex.org/W4233619103","https://openalex.org/W4285719527","https://openalex.org/W4297931263","https://openalex.org/W6624640001","https://openalex.org/W6639377692","https://openalex.org/W6675750237","https://openalex.org/W6684188680","https://openalex.org/W6716767161","https://openalex.org/W6726681274","https://openalex.org/W6729002501"],"related_works":["https://openalex.org/W2037328426","https://openalex.org/W1990914742","https://openalex.org/W2891033441","https://openalex.org/W2006559622","https://openalex.org/W2315521504","https://openalex.org/W3106536224","https://openalex.org/W2890371384","https://openalex.org/W2773863718","https://openalex.org/W2563324120","https://openalex.org/W2040756827"],"abstract_inverted_index":{"In":[0,54],"this":[1],"study,":[2],"we":[3],"propose":[4],"a":[5,45,136],"novel":[6],"single":[7],"image":[8,16],"Bayesian":[9],"super-resolution":[10],"(SR)":[11],"algorithm":[12],"where":[13],"the":[14,19,28,34,41,50,72,85,90,98,112,155,172,176,191,229,233,236,245],"hyperspectral":[15],"(HSI)":[17],"is":[18,31,67,74,92,145,169,183,226],"only":[20],"source":[21],"of":[22,27,80,87,235,241],"information.":[23],"The":[24,76,180],"main":[25,82],"contribution":[26],"proposed":[29,68,77,134,181,230],"approach":[30,66,78],"to":[32,44,56,148,202,209],"convert":[33],"ill-posed":[35],"SR":[36],"reconstruction":[37],"(SRR)":[38],"problem":[39,48],"in":[40,49,89,222,239],"spectral":[42,214,246],"domain":[43],"quadratic":[46],"optimization":[47],"abundance":[51,104,128,157,178],"map":[52],"domain.":[53],"order":[55],"do":[57],"so,":[58],"Markov":[59],"Random":[60],"Field":[61],"(MRF)":[62],"based":[63,139],"energy":[64,140,143],"minimization":[65],"and":[69,100,117,151,175,194,200,217],"proved":[70],"that":[71,228],"solution":[73],"quadratic.":[75],"consists":[79],"five":[81],"steps.":[83],"First,":[84],"number":[86],"endmembers":[88,99,174],"scene":[91],"determined":[93],"using":[94,108,132,171,206],"virtual":[95],"dimensionality.":[96],"Second,":[97],"their":[101],"low":[102],"resolution":[103,126],"maps":[105,129,158],"are":[106,130,159],"computed":[107],"simplex":[109],"identification":[110],"via":[111],"splitted":[113],"augmented":[114],"Lagrangian":[115],"(SISAL)":[116],"fully":[118],"constrained":[119],"least":[120],"squares":[121],"(FCLS)":[122],"algorithms.":[123],"Third,":[124],"high":[125],"(HR)":[127],"obtained":[131],"our":[133],"maximum":[135],"posteriori":[137],"(MAP)":[138],"function.":[141],"This":[142],"function":[144],"minimized":[146],"subject":[147],"smoothness,":[149],"unity":[150],"boundary":[152],"constraints.":[153],"Fourth,":[154],"HR":[156,167],"further":[160],"enhanced":[161,177],"with":[162],"texture":[163],"preserving":[164,244],"methods.":[165],"Finally,":[166],"HSI":[168,188],"reconstructed":[170],"extracted":[173],"maps.":[179],"method":[182,231],"tested":[184],"on":[185],"three":[186],"real":[187],"datasets;":[189],"namely":[190],"Cave,":[192],"Harvard":[193],"Hyperspectral":[195],"Remote":[196],"Sensing":[197],"Scenes":[198],"(HRSS)":[199],"compared":[201],"state-of-the-art":[203],"alternative":[204],"methods":[205,238],"peak":[207],"signal":[208],"noise":[210],"ratio,":[211],"structural":[212],"similarity,":[213],"angle":[215],"mapper":[216],"relative":[218],"dimensionless":[219],"global":[220],"error":[221],"synthesis":[223],"metrics.":[224],"It":[225],"shown":[227],"outperforms":[232],"state":[234],"art":[237],"terms":[240],"quality":[242],"while":[243],"consistency.":[247]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
