{"id":"https://openalex.org/W2150427434","doi":"https://doi.org/10.1109/tip.2014.2317985","title":"Mixed Noise Removal by Weighted Encoding With Sparse Nonlocal Regularization","display_name":"Mixed Noise Removal by Weighted Encoding With Sparse Nonlocal Regularization","publication_year":2014,"publication_date":"2014-04-17","ids":{"openalex":"https://openalex.org/W2150427434","doi":"https://doi.org/10.1109/tip.2014.2317985","mag":"2150427434","pmid":"https://pubmed.ncbi.nlm.nih.gov/24760906"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2014.2317985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2014.2317985","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5009585171","display_name":"Jielin Jiang","orcid":"https://orcid.org/0000-0002-7191-8674"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jielin Jiang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100433899","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-2078-4215"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["Department of Computing, Hong Kong Polytechnic University, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computing, Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100726984","display_name":"Jian Yang","orcid":"https://orcid.org/0000-0003-4800-832X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5009585171"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":10.3796,"has_fulltext":false,"cited_by_count":175,"citation_normalized_percentile":{"value":0.98745904,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"23","issue":"6","first_page":"2651","last_page":"2662"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","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/T10688","display_name":"Image and Signal Denoising Methods","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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9987999796867371,"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/value-noise","display_name":"Value noise","score":0.7522223591804504},{"id":"https://openalex.org/keywords/impulse-noise","display_name":"Impulse noise","score":0.7492307424545288},{"id":"https://openalex.org/keywords/gradient-noise","display_name":"Gradient noise","score":0.7333358526229858},{"id":"https://openalex.org/keywords/additive-white-gaussian-noise","display_name":"Additive white Gaussian noise","score":0.7115784883499146},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6454604268074036},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5751462578773499},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5680952668190002},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5536676645278931},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5359557271003723},{"id":"https://openalex.org/keywords/salt-and-pepper-noise","display_name":"Salt-and-pepper noise","score":0.5329194068908691},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5075424909591675},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4958706796169281},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4941418468952179},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4811902642250061},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4171476662158966},{"id":"https://openalex.org/keywords/dark-frame-subtraction","display_name":"Dark-frame subtraction","score":0.41574805974960327},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40896883606910706},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3254108428955078},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.3137786090373993},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.29988253116607666},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.21293601393699646},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.16687270998954773},{"id":"https://openalex.org/keywords/median-filter","display_name":"Median filter","score":0.15030667185783386},{"id":"https://openalex.org/keywords/noise-floor","display_name":"Noise floor","score":0.1352001428604126}],"concepts":[{"id":"https://openalex.org/C182163834","wikidata":"https://www.wikidata.org/wiki/Q2926529","display_name":"Value noise","level":5,"score":0.7522223591804504},{"id":"https://openalex.org/C127372701","wikidata":"https://www.wikidata.org/wiki/Q16979398","display_name":"Impulse noise","level":3,"score":0.7492307424545288},{"id":"https://openalex.org/C200378446","wikidata":"https://www.wikidata.org/wiki/Q4147391","display_name":"Gradient noise","level":5,"score":0.7333358526229858},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.7115784883499146},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6454604268074036},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5751462578773499},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5680952668190002},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5536676645278931},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5359557271003723},{"id":"https://openalex.org/C113660513","wikidata":"https://www.wikidata.org/wiki/Q849379","display_name":"Salt-and-pepper noise","level":5,"score":0.5329194068908691},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5075424909591675},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4958706796169281},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4941418468952179},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4811902642250061},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4171476662158966},{"id":"https://openalex.org/C1160358","wikidata":"https://www.wikidata.org/wiki/Q861103","display_name":"Dark-frame subtraction","level":5,"score":0.41574805974960327},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40896883606910706},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3254108428955078},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.3137786090373993},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.29988253116607666},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.21293601393699646},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.16687270998954773},{"id":"https://openalex.org/C55352655","wikidata":"https://www.wikidata.org/wiki/Q304247","display_name":"Median filter","level":4,"score":0.15030667185783386},{"id":"https://openalex.org/C187612029","wikidata":"https://www.wikidata.org/wiki/Q17083130","display_name":"Noise floor","level":4,"score":0.1352001428604126},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tip.2014.2317985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2014.2317985","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:24760906","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/24760906","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.639.9825","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.639.9825","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www4.comp.polyu.edu.hk/~cslzhang/paper/WESNR.pdf","raw_type":"text"},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/25059","is_oa":false,"landing_page_url":"http://hdl.handle.net/10397/25059","pdf_url":null,"source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal/Magazine Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1936396850","display_name":null,"funder_award_id":"61233011","funder_id":"https://openalex.org/F4320336125","funder_display_name":"National Science Fund for Distinguished Young Scholars"},{"id":"https://openalex.org/G2848555322","display_name":null,"funder_award_id":"30920140121005","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8055397547","display_name":null,"funder_award_id":"61373063","funder_id":"https://openalex.org/F4320336125","funder_display_name":"National Science Fund for Distinguished Young Scholars"},{"id":"https://openalex.org/G8521262284","display_name":null,"funder_award_id":"61125305","funder_id":"https://openalex.org/F4320336125","funder_display_name":"National Science Fund for Distinguished Young Scholars"},{"id":"https://openalex.org/G8684234662","display_name":null,"funder_award_id":"2014CB349303","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320336125","display_name":"National Science Fund for Distinguished Young Scholars","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W42203131","https://openalex.org/W1555606011","https://openalex.org/W1965735782","https://openalex.org/W1978749115","https://openalex.org/W1999174140","https://openalex.org/W2027616686","https://openalex.org/W2036359163","https://openalex.org/W2037642501","https://openalex.org/W2045079989","https://openalex.org/W2056370875","https://openalex.org/W2061326794","https://openalex.org/W2065742895","https://openalex.org/W2081933987","https://openalex.org/W2085692415","https://openalex.org/W2090356242","https://openalex.org/W2094903560","https://openalex.org/W2099244020","https://openalex.org/W2100249676","https://openalex.org/W2107474456","https://openalex.org/W2117865218","https://openalex.org/W2119883478","https://openalex.org/W2122214262","https://openalex.org/W2122445236","https://openalex.org/W2124139674","https://openalex.org/W2126773133","https://openalex.org/W2136210095","https://openalex.org/W2136396015","https://openalex.org/W2141983208","https://openalex.org/W2142058898","https://openalex.org/W2148358298","https://openalex.org/W2156600062","https://openalex.org/W2157069239","https://openalex.org/W2159558889","https://openalex.org/W2160547390","https://openalex.org/W2160817147","https://openalex.org/W2160924560","https://openalex.org/W2162276649","https://openalex.org/W2165141499","https://openalex.org/W2169733476","https://openalex.org/W2334911726","https://openalex.org/W2349369506","https://openalex.org/W2476868371","https://openalex.org/W2489822048","https://openalex.org/W3022380717","https://openalex.org/W3100830527","https://openalex.org/W3104072696","https://openalex.org/W3104720471","https://openalex.org/W6633105169","https://openalex.org/W6678432518"],"related_works":["https://openalex.org/W2343314293","https://openalex.org/W2144975018","https://openalex.org/W2052906657","https://openalex.org/W2464903433","https://openalex.org/W2980586888","https://openalex.org/W2011016717","https://openalex.org/W2111069477","https://openalex.org/W2736132426","https://openalex.org/W2290428876","https://openalex.org/W2543147290"],"abstract_inverted_index":{"Mixed":[0],"noise":[1,12,31,36,41,45,77,100,164],"removal":[2,46,165],"from":[3],"natural":[4],"images":[5],"is":[6,32,78,105,122],"a":[7,18,23,85,143],"challenging":[8],"task":[9],"since":[10],"the":[11,55,63,75,132,149,157],"distribution":[13],"usually":[14],"does":[15],"not":[16,106],"have":[17],"parametric":[19],"model":[20],"and":[21,60,128,136,146,173],"has":[22],"heavy":[24],"tail.":[25],"One":[26],"typical":[27],"kind":[28],"of":[29,57,110,169],"mixed":[30,44,64,76,99,163],"additive":[33],"white":[34],"Gaussian":[35],"(AWGN)":[37],"coupled":[38],"with":[39,93,126],"impulse":[40,111,116],"(IN).":[42],"Many":[43],"methods":[47,68],"are":[48,140],"detection":[49,118],"based":[50],"methods.":[51],"They":[52],"first":[53],"detect":[54],"locations":[56],"IN":[58,127],"pixels":[59],"then":[61],"remove":[62],"noise.":[65],"However,":[66],"such":[67],"tend":[69],"to":[70,124],"generate":[71],"many":[72],"artifacts":[73],"when":[74],"strong.":[79],"In":[80,102],"this":[81],"paper,":[82],"we":[83],"propose":[84],"simple":[86],"yet":[87],"effective":[88],"method,":[89],"namely":[90],"weighted":[91,120],"encoding":[92,121,151],"sparse":[94],"nonlocal":[95,137],"regularization":[96,144],"(WESNR),":[97],"for":[98],"removal.":[101],"WESNR,":[103],"there":[104],"an":[107],"explicit":[108],"step":[109],"pixel":[112,117],"detection;":[113],"instead,":[114],"soft":[115],"via":[119],"used":[123],"deal":[125],"AWGN":[129],"simultaneously.":[130],"Meanwhile,":[131],"image":[133],"sparsity":[134],"prior":[135,139],"self-similarity":[138],"integrated":[141],"into":[142,148],"term":[145],"introduced":[147],"variational":[150],"framework.":[152],"Experimental":[153],"results":[154],"show":[155],"that":[156],"proposed":[158],"WESNR":[159],"method":[160],"achieves":[161],"leading":[162],"performance":[166],"in":[167],"terms":[168],"both":[170],"quantitative":[171],"measures":[172],"visual":[174],"quality.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":29},{"year":2019,"cited_by_count":23},{"year":2018,"cited_by_count":19},{"year":2017,"cited_by_count":15},{"year":2016,"cited_by_count":13},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}