{"id":"https://openalex.org/W2017514550","doi":"https://doi.org/10.1109/icip.2006.313034","title":"Gradient Adaptive Image Restoration and Enhancement","display_name":"Gradient Adaptive Image Restoration and Enhancement","publication_year":2006,"publication_date":"2006-10-01","ids":{"openalex":"https://openalex.org/W2017514550","doi":"https://doi.org/10.1109/icip.2006.313034","mag":"2017514550"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2006.313034","doi":"https://doi.org/10.1109/icip.2006.313034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2006.313034","pdf_url":null,"source":{"id":"https://openalex.org/S4210223844","display_name":"Proceedings - International Conference on Image Processing","issn_l":"1522-4880","issn":["1522-4880","2381-8549"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 International Conference on Image Processing","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5101753504","display_name":"Hongcheng Wang","orcid":"https://orcid.org/0009-0004-2783-5910","observed_orcids":["https://orcid.org/0009-0004-2783-5910"]},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongcheng Wang","raw_affiliation_strings":["Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001656495","display_name":"Yunqiang Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunqiang Chen","raw_affiliation_strings":["Intelligent Vision and Reasoning Dept, Siemens Corporate Research, Princeton, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Vision and Reasoning Dept, Siemens Corporate Research, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111520035","display_name":"Tong Fang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tong Fang","raw_affiliation_strings":["Intelligent Vision and Reasoning Dept, Siemens Corporate Research, Princeton, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Vision and Reasoning Dept, Siemens Corporate Research, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023072093","display_name":"Jason Tyan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jason Tyan","raw_affiliation_strings":["Intelligent Vision and Reasoning Dept, Siemens Corporate Research, Princeton, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Vision and Reasoning Dept, Siemens Corporate Research, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108521995","display_name":"Narendra Ahuja","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Narendra Ahuja","raw_affiliation_strings":["Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2403,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.88913976,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2893","last_page":"2896"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.5781000256538391,"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":0.5781000256538391,"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":0.41769999265670776,"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":0.0031999999191612005,"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/image-restoration","display_name":"image restoration","score":0.8259999752044678},{"id":"https://openalex.org/keywords/image-enhancement","display_name":"image enhancement","score":0.9990000128746033},{"id":"https://openalex.org/keywords/gradient-domain","display_name":"gradient domain","score":0.9150000214576721},{"id":"https://openalex.org/keywords/poisson-equation","display_name":"Poisson equation","score":0.8429999947547913},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"noise reduction","score":0.8019999861717224},{"id":"https://openalex.org/keywords/contrast-enhancement","display_name":"contrast enhancement","score":0.4569999873638153},{"id":"https://openalex.org/keywords/boundary-enhancement","display_name":"boundary enhancement","score":0.32600000500679016}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6755275726318359},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.6302598714828491},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.544257640838623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5180268883705139},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4711540937423706},{"id":"https://openalex.org/C96716743","wikidata":"https://www.wikidata.org/wiki/Q827688","display_name":"Poisson's equation","level":2,"score":0.460319459438324},{"id":"https://openalex.org/C96133863","wikidata":"https://www.wikidata.org/wiki/Q6913458","display_name":"Morphological gradient","level":5,"score":0.45493564009666443},{"id":"https://openalex.org/C200378446","wikidata":"https://www.wikidata.org/wiki/Q4147391","display_name":"Gradient noise","level":5,"score":0.4480842649936676},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.447672039270401},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43112826347351074},{"id":"https://openalex.org/C182037307","wikidata":"https://www.wikidata.org/wiki/Q17039097","display_name":"Image gradient","level":5,"score":0.42289865016937256},{"id":"https://openalex.org/C184050105","wikidata":"https://www.wikidata.org/wiki/Q273163","display_name":"Isotropy","level":2,"score":0.4106692671775818},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3936856985092163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38411837816238403},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36902058124542236},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33969008922576904},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.24758929014205933},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.23207280039787292},{"id":"https://openalex.org/C55352655","wikidata":"https://www.wikidata.org/wiki/Q304247","display_name":"Median filter","level":4,"score":0.22483384609222412},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.19284868240356445},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.1300855576992035},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.09359535574913025},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icip.2006.313034","doi":"https://doi.org/10.1109/icip.2006.313034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2006.313034","pdf_url":null,"source":{"id":"https://openalex.org/S4210223844","display_name":"Proceedings - International Conference on Image Processing","issn_l":"1522-4880","issn":["1522-4880","2381-8549"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 International Conference on Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.80.2095","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.2095","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vision.ai.uiuc.edu/~wanghc/papers/icip06_grad_filtering.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.91.2399","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.2399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ifp.uiuc.edu/~chenyq/research/publications/ICIP06_grad_filtering.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1542452706","https://openalex.org/W1966786995","https://openalex.org/W2005666551","https://openalex.org/W2106381105","https://openalex.org/W2117853853","https://openalex.org/W2132680427","https://openalex.org/W2133251749","https://openalex.org/W2144451417","https://openalex.org/W2146086273","https://openalex.org/W2146842127","https://openalex.org/W2150134853","https://openalex.org/W2242047952","https://openalex.org/W2432517183","https://openalex.org/W2981264952","https://openalex.org/W2997077506"],"related_works":["https://openalex.org/W2391472404","https://openalex.org/W2135727861","https://openalex.org/W1879291833","https://openalex.org/W2117268221","https://openalex.org/W1979381664","https://openalex.org/W1522047653","https://openalex.org/W2891285668","https://openalex.org/W7062428437","https://openalex.org/W2389048781","https://openalex.org/W3182571006"],"abstract_inverted_index":{"Various":[0],"methods":[1],"have":[2],"been":[3],"proposed":[4],"for":[5],"image":[6,107],"enhancement":[7],"and":[8,136],"restoration.":[9],"The":[10],"main":[11],"difficulty":[12],"is":[13,63,99],"how":[14],"to":[15,66,74],"enhance":[16,50,125],"the":[17,22,34,39,45,51,57,60,75,79,82,88,105,109,126,131,150],"structures":[18],"uniformly":[19,53],"while":[20,85],"suppressing":[21,78],"noise":[23,83,132],"without":[24,54],"artifacts.":[25],"In":[26],"this":[27,31],"paper,":[28],"we":[29,48,68,92],"tackle":[30],"problem":[32],"in":[33,81,142],"gradient":[35,46,61,76,96,111],"domain":[36],"instead":[37],"of":[38,152],"traditional":[40],"intensity":[41],"domain.":[42],"By":[43],"enhancing":[44,86],"field,":[47,77,97],"can":[49,124],"structure":[52],"overshooting":[55],"at":[56],"boundary.":[58],"Because":[59],"field":[62,112],"very":[64],"sensitive":[65],"noise,":[67],"apply":[69],"an":[70],"orientation-isotropy":[71],"adaptive":[72],"filter":[73],"gradients":[80],"regions":[84],"along":[87],"object":[89,127],"boundaries.":[90],"Thus":[91],"obtain":[93],"a":[94,119],"modulated":[95,110],"which":[98],"usually":[100],"not":[101],"integrable.":[102],"We":[103],"reconstruct":[104],"enhanced":[106],"from":[108],"with":[113,133],"least":[114],"square":[115],"errors":[116],"by":[117],"solving":[118],"Poisson":[120],"equation.":[121],"This":[122],"method":[123],"contrast":[128],"uniformly,":[129],"suppress":[130],"no":[134],"artifacts,":[135],"avoid":[137],"setting":[138],"stopping":[139],"time":[140],"as":[141],"PDE":[143],"methods.":[144],"Experiments":[145],"on":[146],"noisy":[147],"images":[148],"show":[149],"efficacy":[151],"our":[153],"method.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}