{"id":"https://openalex.org/W2199199062","doi":null,"title":"A Study of the Structural Similarity Image Quality Measure with Applications to Image Processing","display_name":"A Study of the Structural Similarity Image Quality Measure with Applications to Image Processing","publication_year":2012,"publication_date":"2012-09-07","ids":{"openalex":"https://openalex.org/W2199199062","mag":"2199199062"},"language":"en","primary_location":{"id":"pmh:oai:uwspace.uwaterloo.ca:10012/6982","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/10012/6982","pdf_url":"https://uwspace.uwaterloo.ca/bitstreams/e9e33e50-7e7f-4e03-b470-155372846798/download","source":{"id":"https://openalex.org/S4306401661","display_name":"UWSpace (University of Waterloo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I151746483","host_organization_name":"University of Waterloo","host_organization_lineage":["https://openalex.org/I151746483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Doctoral Thesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://uwspace.uwaterloo.ca/bitstreams/e9e33e50-7e7f-4e03-b470-155372846798/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115069267","display_name":"Dominique Brunet","orcid":"https://orcid.org/0000-0002-5725-0866","observed_orcids":["https://orcid.org/0000-0002-5725-0866"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Dominique Brunet","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-5725-0866","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5115069267"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9843999743461609,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9843999743461609,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.008700000122189522,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.001500000013038516,"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/structural-similarity-index","display_name":"structural similarity index","score":0.8119999766349792},{"id":"https://openalex.org/keywords/image-quality-assessment","display_name":"image quality assessment","score":0.9340000152587891},{"id":"https://openalex.org/keywords/best-approximation","display_name":"best approximation","score":0.6990000009536743},{"id":"https://openalex.org/keywords/point-estimators","display_name":"point estimators","score":0.6019999980926514},{"id":"https://openalex.org/keywords/image-self-similarity","display_name":"image self-similarity","score":0.8870000243186951},{"id":"https://openalex.org/keywords/image-denoising","display_name":"image denoising","score":0.7630000114440918},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"mean squared error","score":0.7110000252723694}],"concepts":[{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.609803318977356},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6032751202583313},{"id":"https://openalex.org/C139489369","wikidata":"https://www.wikidata.org/wiki/Q770846","display_name":"Structural similarity","level":2,"score":0.570202112197876},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5494166016578674},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5341491103172302},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5070412158966064},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4721778929233551},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4421650469303131},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4398241937160492},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.42321568727493286},{"id":"https://openalex.org/C104317675","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Digital image processing","level":4,"score":0.42156556248664856},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.4182095527648926},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38356149196624756},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3826982378959656},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34204402565956116},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:uwspace.uwaterloo.ca:10012/6982","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/10012/6982","pdf_url":"https://uwspace.uwaterloo.ca/bitstreams/e9e33e50-7e7f-4e03-b470-155372846798/download","source":{"id":"https://openalex.org/S4306401661","display_name":"UWSpace (University of Waterloo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I151746483","host_organization_name":"University of Waterloo","host_organization_lineage":["https://openalex.org/I151746483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Doctoral Thesis"},{"id":"mag:2199199062","doi":null,"is_oa":false,"landing_page_url":"https://uwspace.uwaterloo.ca/bitstream/10012/6982/1/Brunet_Dominique.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:uwspace.uwaterloo.ca:10012/6982","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/10012/6982","pdf_url":"https://uwspace.uwaterloo.ca/bitstreams/e9e33e50-7e7f-4e03-b470-155372846798/download","source":{"id":"https://openalex.org/S4306401661","display_name":"UWSpace (University of Waterloo)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I151746483","host_organization_name":"University of Waterloo","host_organization_lineage":["https://openalex.org/I151746483"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Doctoral Thesis"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2199199062.pdf","grobid_xml":"https://content.openalex.org/works/W2199199062.grobid-xml"},"referenced_works_count":90,"referenced_works":["https://openalex.org/W42232744","https://openalex.org/W49968550","https://openalex.org/W1491751692","https://openalex.org/W1494041778","https://openalex.org/W1494442898","https://openalex.org/W1527289589","https://openalex.org/W1541459201","https://openalex.org/W1574700824","https://openalex.org/W1575230410","https://openalex.org/W1589277034","https://openalex.org/W1605525286","https://openalex.org/W1622427076","https://openalex.org/W1969235627","https://openalex.org/W1970642807","https://openalex.org/W1986931325","https://openalex.org/W1992201949","https://openalex.org/W2001726230","https://openalex.org/W2011181254","https://openalex.org/W2024221234","https://openalex.org/W2029091038","https://openalex.org/W2038044292","https://openalex.org/W2040324983","https://openalex.org/W2044475487","https://openalex.org/W2051622516","https://openalex.org/W2056370875","https://openalex.org/W2069912449","https://openalex.org/W2078950386","https://openalex.org/W2079615115","https://openalex.org/W2080130699","https://openalex.org/W2081003258","https://openalex.org/W2081486922","https://openalex.org/W2081839214","https://openalex.org/W2083251471","https://openalex.org/W2088836904","https://openalex.org/W2089144366","https://openalex.org/W2092755522","https://openalex.org/W2093855496","https://openalex.org/W2097074225","https://openalex.org/W2098737227","https://openalex.org/W2098914003","https://openalex.org/W2099474155","https://openalex.org/W2099799750","https://openalex.org/W2100115174","https://openalex.org/W2103559027","https://openalex.org/W2103882108","https://openalex.org/W2103997799","https://openalex.org/W2109761230","https://openalex.org/W2113945798","https://openalex.org/W2114549779","https://openalex.org/W2114582993","https://openalex.org/W2115549875","https://openalex.org/W2116857329","https://openalex.org/W2117787067","https://openalex.org/W2121058967","https://openalex.org/W2121809595","https://openalex.org/W2128659236","https://openalex.org/W2130815094","https://openalex.org/W2133665775","https://openalex.org/W2136227079","https://openalex.org/W2137136191","https://openalex.org/W2141115311","https://openalex.org/W2145096794","https://openalex.org/W2146411623","https://openalex.org/W2146600015","https://openalex.org/W2146766088","https://openalex.org/W2149925139","https://openalex.org/W2150734399","https://openalex.org/W2151693816","https://openalex.org/W2153663612","https://openalex.org/W2158003722","https://openalex.org/W2159372562","https://openalex.org/W2160046865","https://openalex.org/W2160095396","https://openalex.org/W2160547390","https://openalex.org/W2161907179","https://openalex.org/W2162831671","https://openalex.org/W2163285557","https://openalex.org/W2171349048","https://openalex.org/W2171364630","https://openalex.org/W2293143519","https://openalex.org/W2296319761","https://openalex.org/W2296616510","https://openalex.org/W2330590360","https://openalex.org/W2483902856","https://openalex.org/W2492555704","https://openalex.org/W2499334499","https://openalex.org/W2611537933","https://openalex.org/W2626610348","https://openalex.org/W3005363104","https://openalex.org/W4211165038"],"related_works":["https://openalex.org/W2099474155","https://openalex.org/W2293412448","https://openalex.org/W1907847775","https://openalex.org/W6908519765","https://openalex.org/W53174685","https://openalex.org/W3038078907","https://openalex.org/W7024734017","https://openalex.org/W2894468232","https://openalex.org/W2475617956","https://openalex.org/W4289651705"],"abstract_inverted_index":{"Since":[0],"its":[1,70],"introduction":[2],"in":[3,64,92,127,254,299,334],"2004,":[4],"the":[5,28,34,42,59,93,115,119,123,135,158,189,194,224,228,230,240,243,246,262,272,278,287,291,305,316,320,327,330],"Structural":[6],"Similarity":[7],"(SSIM)":[8],"index":[9,121,137,160,289,322],"has":[10],"gained":[11],"widespread":[12],"popularity":[13],"as":[14],"an":[15,265],"image":[16,65,273,309,335],"quality":[17],"assessment":[18,279],"measure.":[19],"SSIM":[20,120,136,159,195,288,321,333],"is":[21,132,161,196,235,275],"currently":[22],"recognized":[23],"to":[24,90,164,193,239,304],"be":[25,139],"one":[26],"of":[27,32,37,55,69,77,95,114,118,157,167,181,227,233,242,249,251,257,267,280,286,307,315,319,329],"most":[29,60],"powerful":[30],"methods":[31],"assessing":[33],"visual":[35],"closeness":[36],"images.":[38,213,282],"That":[39],"being":[40],"said,":[41],"Mean":[43],"Squared":[44],"Error":[45],"(MSE),":[46],"which":[47],"performs":[48],"very":[49],"poorly":[50],"from":[51],"a":[52,75,142,165],"perceptual":[53],"point":[54,218],"view,":[56],"still":[57],"remains":[58],"common":[61],"optimization":[62,183],"criterion":[63],"processing":[66,336],"applications":[67],"because":[68],"relative":[71],"simplicity":[72],"along":[73],"with":[74,105,206,332],"number":[76],"other":[78],"properties":[79,117,151,318],"that":[80,245],"are":[81,98,152,184,209,220,293],"deemed":[82],"important.":[83],"In":[84],"this":[85,128,300],"thesis,":[86],"some":[87],"necessary":[88],"tools":[89],"assist":[91],"design":[94],"SSIM-optimal":[96,217],"algorithms":[97],"developed.":[99,294],"This":[100,237],"work":[101],"combines":[102],"theoretical":[103,125],"developments":[104],"experimental":[106,225],"research":[107,297],"and":[108,149,200,290],"practical":[109,263],"algorithms.":[110,311],"\\n":[111,174,222,260,295],"\\nThe":[112,296],"description":[113],"mathematical":[116,317],"represents":[122,323],"principal":[124],"achievement":[126],"thesis.":[129],"Indeed,":[130],"it":[131],"demonstrated":[133],"how":[134],"can":[138],"transformed":[140],"into":[141],"distance":[143],"metric.":[144],"Local":[145],"convexity,":[146],"quasi-convexity,":[147],"symmetries":[148],"invariance":[150],"also":[153,162,210],"proved.":[154],"The":[155],"study":[156],"generalized":[163],"family":[166],"metrics":[168],"called":[169],"normalized":[170],"(or":[171],"M-relative)":[172],"metrics.":[173],"\\nVarious":[175],"analytical":[176],"techniques":[177],"for":[178,198,216,277],"different":[179],"kinds":[180],"SSIM-based":[182],"then":[185],"devised.":[186],"For":[187],"example,":[188],"best":[190],"approximation":[191],"according":[192],"described":[197],"orthogonal":[199],"redundant":[201],"basis":[202],"sets.":[203],"SSIM-geodesic":[204],"paths":[205],"arclength":[207],"parameterization":[208],"traced":[211],"between":[212],"Finally,":[214],"formulas":[215],"estimators":[219],"obtained.":[221],"\\nOn":[223,261],"side":[226],"research,":[229],"structural":[231],"self-similarity":[232,250],"images":[234,252],"studied.":[236],"leads":[238],"confirmation":[241],"hypothesis":[244],"main":[247],"source":[248],"lies":[253],"their":[255],"regions":[256],"low":[258],"variance.":[259],"side,":[264],"implementation":[266],"local":[268],"statistical":[269],"tests":[270],"on":[271],"residual":[274],"proposed":[276],"denoised":[281],"Also,":[283],"heuristic":[284],"estimations":[285],"MSE":[292,331],"performed":[298],"thesis":[301],"should":[302],"lead":[303],"development":[306],"state-of-the-art":[308],"denoising":[310],"A":[312],"better":[313],"comprehension":[314],"another":[324],"step":[325],"toward":[326],"replacement":[328],"applications.":[337]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}
