{"id":"https://openalex.org/W2942930697","doi":"https://doi.org/10.1177/1550147719847133","title":"CSDK: A Chi-square distribution-Kernel method for image de-noising under the Internet of things big data environment","display_name":"CSDK: A Chi-square distribution-Kernel method for image de-noising under the Internet of things big data environment","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2942930697","doi":"https://doi.org/10.1177/1550147719847133","mag":"2942930697"},"language":"en","primary_location":{"id":"doi:10.1177/1550147719847133","is_oa":true,"landing_page_url":"https://doi.org/10.1177/1550147719847133","pdf_url":null,"source":{"id":"https://openalex.org/S64417657","display_name":"International Journal of Distributed Sensor Networks","issn_l":"1550-1329","issn":["1550-1329","1550-1477"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869","https://openalex.org/P4310320595"],"host_organization_lineage_names":["Hindawi Publishing Corporation","Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Distributed Sensor Networks","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1177/1550147719847133","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113671777","display_name":"Lin Teng","orcid":null},"institutions":[{"id":"https://openalex.org/I32399674","display_name":"Shenyang Normal University","ror":"https://ror.org/05cdfgm80","country_code":"CN","type":"education","lineage":["https://openalex.org/I32399674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Teng","raw_affiliation_strings":["College of Software, Shenyang Normal University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Software, Shenyang Normal University, Shenyang, China","institution_ids":["https://openalex.org/I32399674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100455129","display_name":"Hang Li","orcid":"https://orcid.org/0000-0002-1230-4007"},"institutions":[{"id":"https://openalex.org/I32399674","display_name":"Shenyang Normal University","ror":"https://ror.org/05cdfgm80","country_code":"CN","type":"education","lineage":["https://openalex.org/I32399674"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hang Li","raw_affiliation_strings":["College of Software, Shenyang Normal University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-1230-4007","affiliations":[{"raw_affiliation_string":"College of Software, Shenyang Normal University, Shenyang, China","institution_ids":["https://openalex.org/I32399674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100455129"],"corresponding_institution_ids":["https://openalex.org/I32399674"],"apc_list":{"value":2200,"currency":"USD","value_usd":2200},"apc_paid":{"value":2200,"currency":"USD","value_usd":2200},"fwci":0.812,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.73470023,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":"15","issue":"5","first_page":"155014771984713","last_page":"155014771984713"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","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/T10688","display_name":"Image and Signal Denoising Methods","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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9991999864578247,"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":0.995199978351593,"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/computer-science","display_name":"Computer science","score":0.6367619037628174},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.537976861000061},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.534529447555542},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5317792892456055},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4646648168563843},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4445619583129883},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35179173946380615},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33911532163619995},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.313642293214798}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6367619037628174},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.537976861000061},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.534529447555542},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5317792892456055},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4646648168563843},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4445619583129883},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35179173946380615},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33911532163619995},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.313642293214798},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1177/1550147719847133","is_oa":true,"landing_page_url":"https://doi.org/10.1177/1550147719847133","pdf_url":null,"source":{"id":"https://openalex.org/S64417657","display_name":"International Journal of Distributed Sensor Networks","issn_l":"1550-1329","issn":["1550-1329","1550-1477"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869","https://openalex.org/P4310320595"],"host_organization_lineage_names":["Hindawi Publishing Corporation","Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Distributed Sensor Networks","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:sae:intdis:v:15:y:2019:i:5:p:1550147719847133","is_oa":false,"landing_page_url":"https://journals.sagepub.com/doi/10.1177/1550147719847133","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:1c707dd6665741cdbc995d9231372671","is_oa":true,"landing_page_url":"https://doaj.org/article/1c707dd6665741cdbc995d9231372671","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal of Distributed Sensor Networks, Vol 15 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1177/1550147719847133","is_oa":true,"landing_page_url":"https://doi.org/10.1177/1550147719847133","pdf_url":null,"source":{"id":"https://openalex.org/S64417657","display_name":"International Journal of Distributed Sensor Networks","issn_l":"1550-1329","issn":["1550-1329","1550-1477"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869","https://openalex.org/P4310320595"],"host_organization_lineage_names":["Hindawi Publishing Corporation","Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Distributed Sensor Networks","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W787382797","https://openalex.org/W1546181482","https://openalex.org/W1548566132","https://openalex.org/W2000741468","https://openalex.org/W2046031028","https://openalex.org/W2075770243","https://openalex.org/W2079724595","https://openalex.org/W2118423841","https://openalex.org/W2149492639","https://openalex.org/W2158940042","https://openalex.org/W2159069775","https://openalex.org/W2161061004","https://openalex.org/W2227532598","https://openalex.org/W2310691786","https://openalex.org/W2468506054","https://openalex.org/W2496304207","https://openalex.org/W2506016096","https://openalex.org/W2547812180","https://openalex.org/W2607998022","https://openalex.org/W2610514569","https://openalex.org/W2650922930","https://openalex.org/W2743780012","https://openalex.org/W2745993090","https://openalex.org/W2767547957","https://openalex.org/W2784059657","https://openalex.org/W2791512297","https://openalex.org/W2801024427","https://openalex.org/W2888896501","https://openalex.org/W2890230859","https://openalex.org/W2963780177"],"related_works":["https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2116854923","https://openalex.org/W2750730210","https://openalex.org/W2236974868","https://openalex.org/W4312766348","https://openalex.org/W4233939244","https://openalex.org/W2730764323","https://openalex.org/W2952127465","https://openalex.org/W2028276520"],"abstract_inverted_index":{"Nowadays,":[0],"Internet":[1,30,128],"of":[2,14,20,31,63,70,108,129,173,270],"things":[3,32,130],"not":[4,89],"only":[5],"brings":[6],"promising":[7],"opportunities":[8],"but":[9],"also":[10,285],"faces":[11],"a":[12,18,34,50,57,115,160,242,248,287],"lot":[13,19],"challenges.":[15],"It":[16,284],"attracts":[17],"researchers\u2019":[21],"attention":[22],"and":[23,27,97,197,241,280,292],"has":[24],"important":[25],"economic":[26],"social":[28],"values.":[29],"plays":[33],"key":[35,51],"role":[36],"in":[37,43,53,268],"the":[38,61,68,71,75,105,122,127,142,150,156,169,174,198,211,216,221,225,238,255,298],"big":[39,131],"data":[40,132],"processing,":[41],"especially":[42],"image":[44,54,78,181,185,239],"field.":[45],"Image":[46],"de-noising":[47,72,79,85,93,110,266,300],"still":[48],"is":[49,146,163,166,186,207,234,245],"problem":[52],"pre-processing.":[55],"Considering":[56],"given":[58],"noisy":[59,184,212],"image,":[60],"selection":[62],"thresholds":[64],"should":[65],"significantly":[66],"affect":[67],"quality":[69],"image.":[73,158],"Although":[74],"state-of-the-art":[76,265],"wavelet":[77,117,171,226],"methods":[80],"perform":[81],"better":[82],"than":[83],"other":[84],"methods,":[86,111],"they":[87],"are":[88],"very":[90],"effective":[91],"for":[92,180],"with":[94,98],"different":[95,194],"noises":[96],"redundancy":[99],"convergence":[100],"time,":[101],"sometimes.":[102],"To":[103],"mitigate":[104],"poor":[106],"effect":[107],"traditional":[109],"this":[112,260],"article":[113],"proposes":[114],"new":[116,135],"soft":[118,199,227],"threshold":[119,152,218],"based":[120,202,229],"on":[121,203,230],"Chi-square":[123,143,175,204,231,251],"distribution-Kernel":[124,144,176,205,232,252],"method":[125,136,201,206,233],"under":[126],"environment.":[133],"The":[134],"alternates":[137],"three":[138],"minimization":[139],"steps.":[140],"First,":[141],"model":[145],"constructed":[147],"to":[148,155,168,177,192,209,236,297],"find":[149],"customized":[151,170],"that":[153,259],"corresponds":[154],"de-noised":[157],"Second,":[159],"freedom":[161],"degree":[162],"considered,":[164],"which":[165],"related":[167],"coefficient":[172],"be":[178],"thresholded":[179],"de-noising.":[182],"Here,":[183],"first":[187],"decomposed":[188],"into":[189],"many":[190],"levels":[191],"obtain":[193],"frequency":[195],"bands":[196],"thresholding":[200,228],"used":[208],"remove":[210],"coefficients,":[213],"by":[214,247],"fixing":[215],"optimum":[217],"value":[219],"using":[220],"proposed":[222],"method.":[223,253],"Third,":[224],"adopted":[235],"handle":[237],"de-noising,":[240],"significant":[243],"improvement":[244,295],"obtained":[246],"specially":[249],"developed":[250],"Finally,":[254],"experimental":[256],"results":[257],"illustrate":[258],"computationally":[261],"scalable":[262],"algorithm":[263],"achieves":[264],"performance":[267],"terms":[269],"peak":[271],"signal-to-noise":[272],"ratio,":[273],"normalized":[274],"mean":[275],"square":[276],"error,":[277],"structural":[278],"similarity,":[279],"subjective":[281],"visual":[282],"quality.":[283],"shows":[286],"consistent":[288],"accuracy,":[289],"edge":[290],"preservation,":[291],"detailed":[293],"retention":[294],"compared":[296],"classic":[299],"algorithms.":[301]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":5}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}
