{"id":"https://openalex.org/W7168164256","doi":"https://doi.org/10.1109/access.2026.3712165","title":"Selective Denoising Method for Sample-Inspection Images Using Adaptive Hybrid Prior Analysis","display_name":"Selective Denoising Method for Sample-Inspection Images Using Adaptive Hybrid Prior Analysis","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7168164256","doi":"https://doi.org/10.1109/access.2026.3712165"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3712165","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3712165","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3712165","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063837369","display_name":"Yaohe Li","orcid":"https://orcid.org/0009-0002-9211-1965"},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Liu","raw_affiliation_strings":["China Tobacco Henan Industrial Company Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Tobacco Henan Industrial Company Ltd","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350268","display_name":"Qi Li","orcid":"https://orcid.org/0000-0003-2004-6885"},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Li","raw_affiliation_strings":["China Tobacco Henan Industrial Company Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Tobacco Henan Industrial Company Ltd","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104146290","display_name":"Linchao Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linchao Yang","raw_affiliation_strings":["China Tobacco Henan Industrial Company Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Tobacco Henan Industrial Company Ltd","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136109048","display_name":"Binqiang Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I4750791","display_name":"Henan Agricultural University","ror":"https://ror.org/04eq83d71","country_code":"CN","type":"education","lineage":["https://openalex.org/I4750791"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binqiang Tian","raw_affiliation_strings":["Henan Agricultural University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan Agricultural University","institution_ids":["https://openalex.org/I4750791"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104145789","display_name":"Suijun Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I2800556661","display_name":"China Tobacco","ror":"https://ror.org/030d08e08","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800556661"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suijun Liu","raw_affiliation_strings":["China Tobacco Henan Industrial Company Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Tobacco Henan Industrial Company Ltd","institution_ids":["https://openalex.org/I2800556661"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044304045","display_name":"Y F Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaohe Li","raw_affiliation_strings":["Xi\u2019an University of Technology"],"raw_orcid":"https://orcid.org/0009-0002-9211-1965","affiliations":[{"raw_affiliation_string":"Xi\u2019an University of Technology","institution_ids":["https://openalex.org/I4210131919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.87698159,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"107263","last_page":"107288"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.21299999952316284,"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":0.21299999952316284,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.06989999860525131,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.0640999972820282,"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/noise-reduction","display_name":"Noise reduction","score":0.579800009727478},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5498999953269958},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3952000141143799},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.37869998812675476},{"id":"https://openalex.org/keywords/video-denoising","display_name":"Video denoising","score":0.3450999855995178},{"id":"https://openalex.org/keywords/adaptive-filter","display_name":"Adaptive filter","score":0.30079999566078186}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7394000291824341},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.671999990940094},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.579800009727478},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5498999953269958},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5257999897003174},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3952000141143799},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.37869998812675476},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.3450999855995178},{"id":"https://openalex.org/C102248274","wikidata":"https://www.wikidata.org/wiki/Q168388","display_name":"Adaptive filter","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.29750001430511475},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.29179999232292175},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27630001306533813}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3712165","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3712165","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1c1cd722f4ca43f3ba65dad9e910b640","is_oa":false,"landing_page_url":"https://doaj.org/article/1c1cd722f4ca43f3ba65dad9e910b640","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 107263-107288 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3712165","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3712165","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.4789634346961975,"display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G4278682785","display_name":"\u57fa\u4e8e\u673a\u5668\u5b66\u4e60\u7684\u7cbe\u5bc6\u68c0\u6d4b\u82e5\u5e72\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"51765007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1974438823","https://openalex.org/W2056370875","https://openalex.org/W2099244020","https://openalex.org/W2136396015","https://openalex.org/W2764207251","https://openalex.org/W2772727138","https://openalex.org/W2910620000","https://openalex.org/W2989900256","https://openalex.org/W2990307067","https://openalex.org/W2999182354","https://openalex.org/W3047011367","https://openalex.org/W3186356718","https://openalex.org/W4288801111","https://openalex.org/W4296551003","https://openalex.org/W4312054809","https://openalex.org/W4319878654","https://openalex.org/W4383497778","https://openalex.org/W4388002256","https://openalex.org/W4389302232","https://openalex.org/W4390607423","https://openalex.org/W4390740056","https://openalex.org/W4391152257","https://openalex.org/W4394576755","https://openalex.org/W4396641079","https://openalex.org/W4396734551","https://openalex.org/W4401666634","https://openalex.org/W4402306612","https://openalex.org/W4403288769","https://openalex.org/W4403768124","https://openalex.org/W4405126274","https://openalex.org/W4406328079","https://openalex.org/W4407562131","https://openalex.org/W4410533840","https://openalex.org/W4410595751","https://openalex.org/W4410721821","https://openalex.org/W4411155138","https://openalex.org/W4411393893","https://openalex.org/W4412456627","https://openalex.org/W4413156076","https://openalex.org/W4415551207"],"related_works":[],"abstract_inverted_index":{"Industrial":[0],"sample":[1],"surface-quality":[2,210],"inspection":[3,48],"is":[4,92],"easily":[5],"affected":[6],"by":[7,149,159],"uneven":[8],"illumination,":[9],"slight":[10],"equipment":[11],"vibration,":[12],"and":[13,24,34,36,64,110,121,144,154,173,179,206,223,235,243],"imaging-device":[14],"limitations,":[15],"which":[16],"may":[17,51],"introduce":[18],"mixed":[19],"noise,":[20,59],"obscure":[21],"fine":[22],"details,":[23],"reduce":[25],"detection":[26,211,221],"accuracy.":[27],"Existing":[28],"denoising":[29,77,242],"methods,":[30,38],"including":[31],"smoothing-filter-based,":[32],"deep-learning-based,":[33],"self-supervised":[35],"unsupervised":[37],"can":[39],"suppress":[40],"noise":[41,111,155],"to":[42,98,134],"varying":[43],"degrees;":[44],"however,":[45],"in":[46,55,196],"industrial":[47,245],"scenarios,":[49],"they":[50],"still":[52],"face":[53],"challenges":[54],"simultaneously":[56],"removing":[57],"residual":[58],"preserving":[60],"original":[61,203],"image":[62,97,101,119,204,241],"information,":[63,205],"maintaining":[65],"computational":[66,123,207],"efficiency.":[67,124,208],"To":[68],"address":[69],"these":[70],"issues,":[71],"this":[72],"paper":[73],"proposes":[74],"a":[75],"selective":[76,164],"method":[78,187,231],"for":[79,239],"sample-inspection":[80,181,240],"images":[81,182],"using":[82],"adaptive":[83,88,127,150,160],"hybrid":[84,89],"prior":[85,90],"analysis.":[86],"First,":[87],"analysis":[91],"performed":[93],"on":[94,177],"the":[95,135,168,185,193,217,229],"input":[96],"classify":[99],"local":[100],"blocks":[102,139,146,156],"into":[103],"non-noise":[104,138],"blocks,":[105,107,109,112],"edge":[106,143],"suspected-noise":[108,145],"thereby":[113],"avoiding":[114],"unnecessary":[115],"processing":[116,165],"of":[117,202],"reliable":[118],"regions":[120],"improving":[122],"Then,":[125],"different":[126,180],"filtering":[128],"strategies":[129],"are":[130,140,147,157],"selectively":[131],"applied":[132],"according":[133],"block":[136],"type:":[137],"directly":[141],"preserved,":[142],"processed":[148,158],"weighted":[151],"root-mean-square":[152],"filtering,":[153],"Gaussian":[161],"filtering.":[162],"This":[163],"strategy":[166],"improves":[167,220],"balance":[169],"between":[170],"mixed-noise":[171,197],"suppression":[172],"detail":[174,199],"preservation.":[175],"Experiments":[176],"natural":[178],"show":[183],"that":[184,216],"proposed":[186,218,230],"achieves":[188],"better":[189],"overall":[190],"performance":[191],"than":[192],"compared":[194],"methods":[195],"removal,":[198],"preservation,":[200],"protection":[201],"Furthermore,":[209],"experiments":[212],"with":[213],"YOLOv8":[214],"demonstrate":[215],"preprocessing":[219,237],"accuracy":[222],"stability":[224],"under":[225],"noisy":[226],"conditions.":[227],"Overall,":[228],"provides":[232],"an":[233],"effective":[234],"efficient":[236],"solution":[238],"subsequent":[244],"vision":[246],"inspection.":[247]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-07-14T00:00:00"}