{"id":"https://openalex.org/W2752540562","doi":"https://doi.org/10.1109/icmew.2017.8026240","title":"Single image detail enhancement via residual homogeneity","display_name":"Single image detail enhancement via residual homogeneity","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2752540562","doi":"https://doi.org/10.1109/icmew.2017.8026240","mag":"2752540562"},"language":"en","primary_location":{"id":"doi:10.1109/icmew.2017.8026240","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2017.8026240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)","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/A5100623154","display_name":"He Jiang","orcid":"https://orcid.org/0000-0002-1562-7426"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"He Jiang","raw_affiliation_strings":["Shanghai Jiaotong University"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiaotong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064168853","display_name":"Guangtao Zhai","orcid":"https://orcid.org/0000-0001-8165-9322"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangtao Zhai","raw_affiliation_strings":["Shanghai Jiaotong University"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiaotong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100404947","display_name":"Jie Yang","orcid":"https://orcid.org/0000-0003-4801-7162"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Yang","raw_affiliation_strings":["Shanghai Jiaotong University"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiaotong University","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100623154"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11920427,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"238","last_page":"242"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":1.0,"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":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9998000264167786,"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":0.9998000264167786,"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/residual","display_name":"Residual","score":0.8844775557518005},{"id":"https://openalex.org/keywords/homogeneity","display_name":"Homogeneity (statistics)","score":0.8563365936279297},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6857377886772156},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.5731686949729919},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4893157184123993},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45417946577072144},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3228223919868469},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21926730871200562},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14436236023902893},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12370792031288147}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8844775557518005},{"id":"https://openalex.org/C142259097","wikidata":"https://www.wikidata.org/wiki/Q5891314","display_name":"Homogeneity (statistics)","level":2,"score":0.8563365936279297},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6857377886772156},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.5731686949729919},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4893157184123993},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45417946577072144},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3228223919868469},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21926730871200562},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14436236023902893},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12370792031288147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmew.2017.8026240","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2017.8026240","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1976416062","https://openalex.org/W2039539938","https://openalex.org/W2048801036","https://openalex.org/W2051865507","https://openalex.org/W2057145757","https://openalex.org/W2099244020","https://openalex.org/W2125188192","https://openalex.org/W2141957843","https://openalex.org/W2160956336","https://openalex.org/W2342044415"],"related_works":["https://openalex.org/W1999392235","https://openalex.org/W2051487156","https://openalex.org/W2075537321","https://openalex.org/W2055668825","https://openalex.org/W2059493168","https://openalex.org/W2371593620","https://openalex.org/W2156037511","https://openalex.org/W2572678357","https://openalex.org/W2019481703","https://openalex.org/W2024930283"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,24,51],"put":[4],"forward":[5],"a":[6,20,53,60,119],"novel":[7],"method":[8],"in":[9,30,35],"single":[10,61],"image":[11,62],"detail":[12,57],"enhancement-":[13],"residual":[14,36,49,64],"homogeneity":[15,18],"(RH).":[16],"Residual":[17],"is":[19,63,100,123,155],"statistic":[21],"result":[22],"when":[23],"test":[25],"different":[26],"kinds":[27],"of":[28,59,80,149],"blocks":[29,34],"database,":[31],"finding":[32],"that":[33,42,56,86,152],"images":[37,74,106,114],"are":[38,45,75],"with":[39,107,118,157],"similar":[40],"structure,":[41],"is,":[43],"they":[44],"homogenous.":[46],"Based":[47],"on":[48],"homogeneity,":[50],"make":[52],"simple":[54],"assumption":[55],"layer":[58],"component":[65],"after":[66],"fast":[67],"in-place":[68],"search":[69],"and":[70,132,162],"block":[71],"match.":[72],"Then":[73],"enhanced":[76],"by":[77,91],"applying":[78],"framework":[79],"RH.":[81],"Unlike":[82],"many":[83,103],"popular":[84,137],"algorithms":[85,104],"need":[87],"to":[88,94,126],"adjust":[89],"parameters":[90],"manual":[92],"operation":[93],"get":[95],"best":[96],"performance,":[97],"our":[98,110,153],"approach":[99],"adaptive.":[101],"Besides,":[102],"output":[105],"intensity":[108],"change,":[109],"RH":[111,122],"can":[112,141],"keep":[113],"from":[115],"over":[116],"enhancement":[117],"nature":[120],"look.":[121],"also":[124],"robust":[125,156],"low":[127],"bit":[128],"rate":[129],"H.265":[130],"system":[131],"runs":[133],"faster":[134],"than":[135],"most":[136],"methods.":[138],"Moreover,":[139],"it":[140],"be":[142],"easily":[143],"FPGA":[144],"implemented":[145],"as":[146],"well.":[147],"Numbers":[148],"experiments":[150],"testify":[151],"algorithm":[154],"good":[158],"performance":[159],"both":[160],"subjectively":[161],"objectively.":[163]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}