{"id":"https://openalex.org/W1984684500","doi":"https://doi.org/10.1109/iccvw.2011.6130325","title":"Perceptually motivated automatic sharpness enhancement using hierarchy of non-local means","display_name":"Perceptually motivated automatic sharpness enhancement using hierarchy of non-local means","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W1984684500","doi":"https://doi.org/10.1109/iccvw.2011.6130325","mag":"1984684500"},"language":"en","primary_location":{"id":"doi:10.1109/iccvw.2011.6130325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw.2011.6130325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5075660915","display_name":"Anustup Choudhury","orcid":"https://orcid.org/0000-0001-6618-9211"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anustup Choudhury","raw_affiliation_strings":["Department of Computer Science, University of Southern California, Los Angeles, CA, USA","University of Southern California, Department of Computer Science, Los Angeles, 90089. USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"University of Southern California, Department of Computer Science, Los Angeles, 90089. USA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006918685","display_name":"G\u00e9rard Medioni","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gerard Medioni","raw_affiliation_strings":["Department of Computer Science, University of Southern California, Los Angeles, CA, USA","University of Southern California, Department of Computer Science, Los Angeles, 90089. USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"University of Southern California, Department of Computer Science, Los Angeles, 90089. USA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"730","last_page":"737"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9997000098228455,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9997000098228455,"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":0.9991999864578247,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9980000257492065,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7179791927337646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6938525438308716},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6240413784980774},{"id":"https://openalex.org/keywords/bilateral-filter","display_name":"Bilateral filter","score":0.5552352666854858},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5532808899879456},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.52406907081604},{"id":"https://openalex.org/keywords/gaussian-filter","display_name":"Gaussian filter","score":0.514679491519928},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4956728219985962},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.44826918840408325},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.42992013692855835},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3862035572528839}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7179791927337646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6938525438308716},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6240413784980774},{"id":"https://openalex.org/C156140930","wikidata":"https://www.wikidata.org/wiki/Q860417","display_name":"Bilateral filter","level":3,"score":0.5552352666854858},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5532808899879456},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.52406907081604},{"id":"https://openalex.org/C65892221","wikidata":"https://www.wikidata.org/wiki/Q1113935","display_name":"Gaussian filter","level":3,"score":0.514679491519928},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4956728219985962},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.44826918840408325},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.42992013692855835},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3862035572528839},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccvw.2011.6130325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw.2011.6130325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1514015969","https://openalex.org/W1574971735","https://openalex.org/W1977973479","https://openalex.org/W2006269342","https://openalex.org/W2017399967","https://openalex.org/W2023292900","https://openalex.org/W2040334833","https://openalex.org/W2067191022","https://openalex.org/W2080592425","https://openalex.org/W2096768337","https://openalex.org/W2099244020","https://openalex.org/W2103504761","https://openalex.org/W2109501488","https://openalex.org/W2113750924","https://openalex.org/W2115683997","https://openalex.org/W2126043703","https://openalex.org/W2130582503","https://openalex.org/W2139312536","https://openalex.org/W2141957843","https://openalex.org/W2145367339","https://openalex.org/W2145744030","https://openalex.org/W2156626530","https://openalex.org/W2244684328","https://openalex.org/W2623277913","https://openalex.org/W3138446083","https://openalex.org/W3139167831","https://openalex.org/W4244317053","https://openalex.org/W4252684946","https://openalex.org/W4255455561","https://openalex.org/W6658085650","https://openalex.org/W6674427960","https://openalex.org/W6681520946"],"related_works":["https://openalex.org/W1998728244","https://openalex.org/W233850645","https://openalex.org/W1999667596","https://openalex.org/W2369676483","https://openalex.org/W4297891612","https://openalex.org/W2082304850","https://openalex.org/W3088540525","https://openalex.org/W1984713107","https://openalex.org/W4285172075","https://openalex.org/W2071879770"],"abstract_inverted_index":{"We":[0,59,94,127],"address":[1],"the":[2,91],"problem":[3],"of":[4,7],"sharpness":[5,66,159,173],"enhancement":[6,142],"images.":[8],"Existing":[9],"hierarchical":[10,70,92],"techniques":[11,36,49],"that":[12],"decompose":[13],"an":[14,87,96],"image":[15,19,63],"into":[16],"a":[17,61,69,73,154],"smooth":[18],"and":[20,28,53,101,137,141,183],"high":[21],"frequency":[22],"components":[23],"based":[24,37,67],"on":[25,38,68,147],"Gaussian":[26],"filter":[27,30,100],"bilateral":[29,125],"suffer":[31],"from":[32],"halo":[33,107],"effects,":[34],"whereas":[35],"weighted":[39],"least":[40],"squares":[41],"extract":[42],"low":[43],"contrast":[44],"features":[45],"as":[46],"detail.":[47],"Other":[48],"require":[50],"multiple":[51],"images":[52,178,186],"are":[54,112,122],"not":[55,116,188],"tolerant":[56],"to":[57,64,79,104,124,157,164,170,179,187],"noise.":[58],"use":[60,95],"single":[62],"enhance":[65],"framework":[71],"using":[72,86,143],"modified":[74],"Laplacian":[75],"pyramid.":[76],"In":[77],"order":[78,169],"ensure":[80],"robustness,":[81],"we":[82,152],"remove":[83,105],"noise":[84],"by":[85,149],"extra":[88],"level":[89],"in":[90,168],"framework.":[93],"edge-preserving":[97],"Non-Local":[98],"Means":[99],"modify":[102],"it":[103],"potential":[106],"effects.":[108],"However,":[109],"these":[110],"effects":[111],"only":[113],"reduced":[114],"but":[115],"removed":[117],"completely":[118],"after":[119],"similar":[120],"modifications":[121],"made":[123],"filter.":[126],"compare":[128],"our":[129,144],"results":[130],"with":[131],"existing":[132],"techniques,":[133],"including":[134],"commercial":[135],"packages":[136],"show":[138],"better":[139],"decomposition":[140],"method.":[145],"Based":[146],"validation":[148],"human":[150],"observers,":[151],"introduce":[153],"new":[155],"measure":[156],"quantify":[158],"quality,":[160],"which":[161],"allows":[162],"us":[163],"automatically":[165],"set":[166],"parameters":[167],"achieve":[171],"preferred":[172],"enhancement.":[174],"This":[175],"causes":[176],"blurry":[177],"be":[180,189],"sharpened":[181],"more":[182],"sufficiently":[184],"sharp":[185],"sharpened.":[190]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
