{"id":"https://openalex.org/W2032784672","doi":"https://doi.org/10.1109/bmei.2011.6098352","title":"Unwrapping Hartmann-Shack images of off-axis aberration using artificial centroid injection method","display_name":"Unwrapping Hartmann-Shack images of off-axis aberration using artificial centroid injection method","publication_year":2011,"publication_date":"2011-10-01","ids":{"openalex":"https://openalex.org/W2032784672","doi":"https://doi.org/10.1109/bmei.2011.6098352","mag":"2032784672"},"language":"en","primary_location":{"id":"doi:10.1109/bmei.2011.6098352","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmei.2011.6098352","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 4th International Conference on Biomedical Engineering and Informatics (BMEI)","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/A5073644414","display_name":"Mitchell Yuwono","orcid":"https://orcid.org/0000-0002-0824-8233"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Mitchell Yuwono","raw_affiliation_strings":["Faculty of Engineering and Information Technology, University of Technology, Sydney, Sydney, NSW, Australia","Faculty of Engineering and Information Technology University of Technology Sydney Sydney New South Wales Australia"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Information Technology, University of Technology, Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]},{"raw_affiliation_string":"Faculty of Engineering and Information Technology University of Technology Sydney Sydney New South Wales Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5073644414"],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":0.657,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69864578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"560","last_page":"564"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11484","display_name":"Adaptive optics and wavefront sensing","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11484","display_name":"Adaptive optics and wavefront sensing","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9828000068664551,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9747999906539917,"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/centroid","display_name":"Centroid","score":0.9201985001564026},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6585620641708374},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5046678781509399},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5005538463592529},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4978809356689453},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46641433238983154},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.43510955572128296},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39535781741142273},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38567060232162476},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2088024616241455}],"concepts":[{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.9201985001564026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6585620641708374},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5046678781509399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5005538463592529},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4978809356689453},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46641433238983154},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.43510955572128296},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39535781741142273},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38567060232162476},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2088024616241455}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bmei.2011.6098352","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bmei.2011.6098352","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 4th International Conference on Biomedical Engineering and Informatics (BMEI)","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/19271","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/19271","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W99725180","https://openalex.org/W1133564852","https://openalex.org/W2076552417","https://openalex.org/W2109364787","https://openalex.org/W2145712193","https://openalex.org/W2145938889","https://openalex.org/W2148024723","https://openalex.org/W2149723649","https://openalex.org/W2154698164","https://openalex.org/W2168237413"],"related_works":["https://openalex.org/W2381926679","https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2116854923","https://openalex.org/W2750730210","https://openalex.org/W2007009951","https://openalex.org/W2236974868","https://openalex.org/W4312766348","https://openalex.org/W4233939244","https://openalex.org/W2173183831"],"abstract_inverted_index":{"As":[0],"the":[1,33,43,75,78,106,136,193],"degree":[2],"of":[3,13,55,67,77,109,122,192],"aberration":[4,170],"and":[5,30,58,80,112,144],"noise":[6],"increases,":[7],"particularly":[8],"for":[9],"off-axis":[10,169],"aberration,":[11],"wavefronts":[12],"Hartmann-Shack":[14],"images":[15],"become":[16],"so":[17],"distorted":[18],"that":[19,116],"special":[20],"care":[21],"needs":[22],"to":[23,28,96,135,140,153,157,176,181],"be":[24],"considered":[25],"in":[26,190],"order":[27],"successfully":[29,165],"gracefully":[31],"unwrap":[32],"images.":[34,195],"This":[35,162],"paper":[36],"proposes":[37],"an":[38,119],"alternative":[39],"algorithmic":[40],"approach":[41],"called":[42],"artificial":[44,131],"centroid":[45,49,82,98,138],"injection":[46],"method.":[47],"Initial":[48],"extraction":[50],"is":[51,150],"done":[52],"using":[53,65,84],"Laplacian":[54],"Gaussian":[56],"(LoG)":[57],"dynamic":[59],"thresholding.":[60],"Outlier":[61],"centroids":[62,101,132,156],"are":[63,93,102,133],"filtered":[64],"ensemble":[66],"weak":[68],"classifiers":[69],"boosted":[70],"with":[71,125,186],"Adaboost":[72],"algorithm.":[73],"Observing":[74],"nature":[76],"vertical":[79,111],"horizontal":[81,113],"sequences":[83,115],"Kalman":[85],"Filter,":[86],"multiple":[87],"General":[88],"Regression":[89],"Neural":[90],"Networks":[91],"(GRNN)":[92],"then":[94,151],"trained":[95],"approximate":[97],"sequences.":[99],"Artificial":[100],"generated":[103],"by":[104],"taking":[105],"intersection":[107],"points":[108],"approximated":[110],"GRNN":[114],"occurs":[117],"inside":[118],"elliptical":[120],"Region":[121],"Interest":[123],"optimized":[124],"Regrouping":[126],"Particle":[127],"Swarm":[128],"(RegPSO).":[129],"These":[130],"injected":[134],"intial":[137],"vector":[139],"predictively":[141],"recover":[142],"missing":[143],"previously":[145],"unrecognized":[146],"spots.":[147],"Wavefront":[148],"algorithm":[149,163],"applied":[152],"correspond":[154],"detected":[155],"their":[158],"appropriate":[159],"lenslet":[160],"centers.":[161],"has":[164],"unwrapped":[166],"29":[167],"different":[168],"HS":[171],"images,":[172],"-50\u00b0":[173],"Temporal":[174],"plane":[175,179],"+50\u00b0":[177],"Nasal":[178],"up":[180],"zero":[182],"pixel":[183],"prediction":[184],"error,":[185],"no":[187],"false":[188],"correlations":[189],"any":[191],"tested":[194]},"counts_by_year":[{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
