{"id":"https://openalex.org/W2167635673","doi":"https://doi.org/10.1109/tgrs.2009.2031636","title":"Super Resolution for Remote Sensing Images Based on a Universal Hidden Markov Tree Model","display_name":"Super Resolution for Remote Sensing Images Based on a Universal Hidden Markov Tree Model","publication_year":2009,"publication_date":"2009-11-06","ids":{"openalex":"https://openalex.org/W2167635673","doi":"https://doi.org/10.1109/tgrs.2009.2031636","mag":"2167635673"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2009.2031636","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2009.2031636","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","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/A5100448847","display_name":"Feng Li","orcid":"https://orcid.org/0000-0001-9945-6208"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Feng Li","raw_affiliation_strings":["School of Information Technology and Electrical Engineering, University of New South Wales, Canberra, ACT, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology and Electrical Engineering, University of New South Wales, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024631382","display_name":"Xiuping Jia","orcid":"https://orcid.org/0000-0001-9916-6382"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xiuping Jia","raw_affiliation_strings":["School of Information Technology and Electrical Engineering, University of New South Wales, Canberra, ACT, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology and Electrical Engineering, University of New South Wales, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086795817","display_name":"Donald Fraser","orcid":"https://orcid.org/0000-0003-0102-9342"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"D. Fraser","raw_affiliation_strings":["School of Information Technology and Electrical Engineering, University of New South Wales, Canberra, ACT, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology and Electrical Engineering, University of New South Wales, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072459625","display_name":"Andrew Lambert","orcid":"https://orcid.org/0000-0003-0390-4446"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"A. Lambert","raw_affiliation_strings":["School of Information Technology and Electrical Engineering, University of New South Wales, Canberra, ACT, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology and Electrical Engineering, University of New South Wales, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5864,"has_fulltext":false,"cited_by_count":99,"citation_normalized_percentile":{"value":0.91157967,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"48","issue":"3","first_page":"1270","last_page":"1278"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9983000159263611,"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":0.9969000220298767,"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/panchromatic-film","display_name":"Panchromatic film","score":0.7835913896560669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7166318297386169},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.682338535785675},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5772268176078796},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5590218305587769},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.545470118522644},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5408336520195007},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.508545994758606},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4911775290966034},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4852423667907715},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4709276556968689},{"id":"https://openalex.org/keywords/gaussian-network-model","display_name":"Gaussian network model","score":0.46000009775161743},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4418230652809143},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.43351489305496216},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21217688918113708},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.16115358471870422},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.07796630263328552}],"concepts":[{"id":"https://openalex.org/C107445234","wikidata":"https://www.wikidata.org/wiki/Q280995","display_name":"Panchromatic film","level":3,"score":0.7835913896560669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7166318297386169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.682338535785675},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5772268176078796},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5590218305587769},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.545470118522644},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5408336520195007},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.508545994758606},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4911775290966034},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4852423667907715},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4709276556968689},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.46000009775161743},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4418230652809143},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.43351489305496216},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21217688918113708},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.16115358471870422},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.07796630263328552},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2009.2031636","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2009.2031636","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W51240228","https://openalex.org/W1584320927","https://openalex.org/W1811400895","https://openalex.org/W2016598597","https://openalex.org/W2031749471","https://openalex.org/W2032260377","https://openalex.org/W2047280020","https://openalex.org/W2067042811","https://openalex.org/W2087380704","https://openalex.org/W2099864919","https://openalex.org/W2102621306","https://openalex.org/W2104609147","https://openalex.org/W2115548755","https://openalex.org/W2126739786","https://openalex.org/W2134929491","https://openalex.org/W2138714160","https://openalex.org/W2140611763","https://openalex.org/W2142856294","https://openalex.org/W2156930033","https://openalex.org/W2165939075","https://openalex.org/W2168796889","https://openalex.org/W2987004640","https://openalex.org/W6634881783","https://openalex.org/W6678578519"],"related_works":["https://openalex.org/W1527867818","https://openalex.org/W2138865713","https://openalex.org/W2541950815","https://openalex.org/W2041159537","https://openalex.org/W2075546197","https://openalex.org/W2154121687","https://openalex.org/W2539985974","https://openalex.org/W2130232481","https://openalex.org/W2164918837","https://openalex.org/W2153230668"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,14,18,38,47,69,98],"new":[6,88],"super":[7,43],"resolution":[8],"(SR)":[9],"method":[10,89,122],"called":[11],"the":[12,59,81],"maximum":[13],"posteriori":[15],"based":[16],"on":[17,114],"universal":[19],"Hidden":[20],"Markov":[21],"Tree":[22],"(HMT)":[23],"model":[24,40,75],"for":[25,41],"remote":[26],"sensing":[27],"images.":[28,57],"The":[29,87],"HMT":[30,74],"theory":[31],"is":[32,76,90],"first":[33,92],"used":[34],"to":[35,79],"set":[36],"up":[37],"prior":[39],"reconstructing":[42],"resolved":[44],"images":[45,63,112],"from":[46,97,108],"sequence":[48],"of":[49,62],"warped,":[50],"blurred,":[51],"subsampled,":[52],"and":[53,129],"noise-contaminated":[54],"low-resolution":[55],"(LR)":[56],"Because":[58],"wavelet":[60,85],"coefficients":[61],"can":[64],"be":[65],"well":[66],"characterized":[67],"as":[68],"mixed":[70],"Gaussian":[71],"distribution,":[72],"an":[73],"better":[77,124],"able":[78],"capture":[80],"dependences":[82],"between":[83],"multiscale":[84],"coefficients.":[86],"tested":[91],"against":[93],"simulated":[94],"LR":[95],"views":[96],"single":[99],"Landsat7":[100,110],"panchromatic":[101,111],"scene":[102],"and,":[103],"then,":[104],"with":[105],"actual":[106],"data":[107],"four":[109],"captured":[113],"different":[115],"dates.":[116],"Both":[117],"tests":[118],"show":[119],"that":[120],"our":[121],"achieves":[123],"SR":[125],"results":[126],"both":[127],"visually":[128],"quantitatively":[130],"than":[131],"other":[132],"methods.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}