{"id":"https://openalex.org/W2157695566","doi":"https://doi.org/10.1109/grc.2006.1635892","title":"Contrast enhancement for image with non-linear gray transform and wavelet neural network","display_name":"Contrast enhancement for image with non-linear gray transform and wavelet neural network","publication_year":2006,"publication_date":"2006-06-08","ids":{"openalex":"https://openalex.org/W2157695566","doi":"https://doi.org/10.1109/grc.2006.1635892","mag":"2157695566"},"language":"en","primary_location":{"id":"doi:10.1109/grc.2006.1635892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/grc.2006.1635892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE International Conference on Granular Computing","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/A5071898642","display_name":"Changjiang Zhang","orcid":"https://orcid.org/0000-0002-2170-3878"},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changjiang Zhang","raw_affiliation_strings":["College of Information Science and Engineering, Zhejiang Normal University, ZJNU, Jinhua, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Zhejiang Normal University, ZJNU, Jinhua, China","institution_ids":["https://openalex.org/I135237710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100382658","display_name":"Xiaodong Wang","orcid":"https://orcid.org/0000-0002-2945-9240"},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Wang","raw_affiliation_strings":["College of Information Science and Engineering, Zhejiang Normal University, ZJNU, Jinhua, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Zhejiang Normal University, ZJNU, Jinhua, China","institution_ids":["https://openalex.org/I135237710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100340490","display_name":"Haoran Zhang","orcid":"https://orcid.org/0000-0002-6883-1375"},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Zhang","raw_affiliation_strings":["College of Information Science and Engineering, Zhejiang Normal University, ZJNU, Jinhua, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Zhejiang Normal University, ZJNU, Jinhua, China","institution_ids":["https://openalex.org/I135237710"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101977309","display_name":"Guojun Lv","orcid":"https://orcid.org/0000-0002-6245-7909"},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"G. Lv","raw_affiliation_strings":["College of Information Science and Engineering, Zhejiang Normal University, ZJNU, Jinhua, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Zhejiang Normal University, ZJNU, Jinhua, China","institution_ids":["https://openalex.org/I135237710"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19132492,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"675","last_page":"678"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9997000098228455,"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":0.9979000091552734,"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/contrast","display_name":"Contrast (vision)","score":0.6073898077011108},{"id":"https://openalex.org/keywords/top-hat-transform","display_name":"Top-hat transform","score":0.5956103801727295},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5884247422218323},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5577728748321533},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.50328129529953},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4871689975261688},{"id":"https://openalex.org/keywords/gray-level","display_name":"Gray level","score":0.45784372091293335},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45368990302085876},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43381351232528687},{"id":"https://openalex.org/keywords/simulated-annealing","display_name":"Simulated annealing","score":0.4209640622138977},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3642972707748413},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35912686586380005},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.2774680256843567},{"id":"https://openalex.org/keywords/digital-image","display_name":"Digital image","score":0.1925351917743683}],"concepts":[{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.6073898077011108},{"id":"https://openalex.org/C180064427","wikidata":"https://www.wikidata.org/wiki/Q2880017","display_name":"Top-hat transform","level":5,"score":0.5956103801727295},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5884247422218323},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5577728748321533},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.50328129529953},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4871689975261688},{"id":"https://openalex.org/C2985861186","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Gray level","level":3,"score":0.45784372091293335},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45368990302085876},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43381351232528687},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.4209640622138977},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3642972707748413},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35912686586380005},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.2774680256843567},{"id":"https://openalex.org/C42781572","wikidata":"https://www.wikidata.org/wiki/Q1250322","display_name":"Digital image","level":4,"score":0.1925351917743683}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/grc.2006.1635892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/grc.2006.1635892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE International Conference on Granular Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1622620102","https://openalex.org/W1975186406","https://openalex.org/W2091452795","https://openalex.org/W2128926607","https://openalex.org/W2157350782","https://openalex.org/W2366731175","https://openalex.org/W7024663340"],"related_works":["https://openalex.org/W2147816597","https://openalex.org/W2312819198","https://openalex.org/W2006268884","https://openalex.org/W2094619061","https://openalex.org/W2129368547","https://openalex.org/W2022136933","https://openalex.org/W3175032145","https://openalex.org/W3107295340","https://openalex.org/W3149790529","https://openalex.org/W3036032503"],"abstract_inverted_index":{"A":[0,258],"new":[1,45,58,113,140,176,194,212,256,295],"contrast":[2,68,91,148],"enhancement":[3,92,158],"algorithm":[4,37,141,153,177],"for":[5,51,89,149,205,215,291],"image":[6,53,150,207,217,253],"is":[7,22,47,54,62,109,129,142,169,183,196,208,218,262,275,299],"proposed":[8,130,197,300],"with":[9],"non-linear":[10,26,266,281],"gray":[11,27,97,200,245],"transform":[12,20,28,80,98,267,282],"and":[13,78,161,165,181,189,243],"wavelet":[14],"neural":[15],"network":[16],"(WNN).":[17],"In-complete":[18],"Beta":[19],"(IBT)":[21],"used":[23,263,276],"to":[24,39,66,84,118,131,144,254,264,277,286,301],"obtain":[25,40],"curve.":[29],"Transform":[30],"parameters":[31,72,99],"are":[32,163],"determined":[33,55,209],"by":[34,111,273],"simulated":[35],"annealing":[36],"(SA)":[38],"optimal":[41,96,280],"s":[42],"space,":[43],"a":[44,125,175,193,255,294],"criterion":[46,195],"proposed.":[48,184],"Contrast":[49,203,214],"type":[50,204],"original":[52,206,216,252],"employing":[56,178,210],"the":[57,86,101,112,122,133,139,147,152,211,279,288,303,306],"criterion.":[59,213],"Parameters":[60],"space":[61,73],"given":[63,272],"respectively":[64],"according":[65],"different":[67],"types,":[69],"which":[70,94,270],"shrinks":[71],"greatly.":[74],"Thus":[75],"searching":[76],"direction":[77],"selegray":[79],"parameters.":[81,268,283],"In":[82,116,284],"order":[83,117,285],"avoid":[85],"expensive":[87],"time":[88],"traditional":[90],"algorithms,":[93],"search":[95],"in":[100,121,305],"whole":[102,123,307],"parameterction":[103],"of":[104,107,127,191,297],"initial":[105],"values":[106],"SA":[108,180],"guided":[110],"parameter":[114],"space.":[115,257],"calculate":[119],"IBT":[120,249,304],"image,":[124],"kind":[126,296],"WNN":[128,182,298],"approximate":[132,302],"IBT.":[134],"Experimental":[135],"results":[136],"show":[137],"that":[138],"able":[143],"adaptively":[145],"enhance":[146],"well.":[151],"was":[154,271],"large.":[155],"Existing":[156],"many":[157],"algorithms'":[159],"intelligence":[160,190],"adaptability":[162],"worse":[164],"much":[166],"artificial":[167],"interference":[168],"required.":[170],"To":[171,185],"solve":[172],"above":[173],"problems,":[174],"IBT,":[179,293],"improve":[186],"optimization":[187],"speed":[188],"algorithm,":[192],"based":[198],"on":[199],"level":[201,246],"histogram.":[202],"classified":[219],"into":[220],"seven":[221],"types:":[222],"particular":[223,240],"dark":[224,227,230],"(PD),":[225],"medium":[226,229,233,237],"(MD),":[228],"slightly":[231,235],"(MDS),":[232],"bright":[234,238,241],"(MBS),":[236],"(MB),":[239],"(PB)":[242],"good":[244],"distribution":[247],"(GGLD).":[248],"operator":[250],"transforms":[251],"certain":[259],"objective":[260],"function":[261],"optimize":[265],"SA,":[269],"William,":[274],"determine":[278],"reduce":[287],"computation":[289],"burden":[290],"calculating":[292],"image.":[308]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
