{"id":"https://openalex.org/W4378231424","doi":"https://doi.org/10.3390/computers12060112","title":"Image Denoising by Deep Convolution Based on Sparse Representation","display_name":"Image Denoising by Deep Convolution Based on Sparse Representation","publication_year":2023,"publication_date":"2023-05-24","ids":{"openalex":"https://openalex.org/W4378231424","doi":"https://doi.org/10.3390/computers12060112"},"language":"en","primary_location":{"id":"doi:10.3390/computers12060112","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers12060112","pdf_url":"https://www.mdpi.com/2073-431X/12/6/112/pdf?version=1685012758","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-431X/12/6/112/pdf?version=1685012758","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027152461","display_name":"Shengqin Bian","orcid":"https://orcid.org/0000-0002-6893-9992"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengqin Bian","raw_affiliation_strings":["School of Automation, University of Science and Technology Beijing, Beijing 100083, China"],"raw_orcid":"https://orcid.org/0000-0002-6893-9992","affiliations":[{"raw_affiliation_string":"School of Automation, University of Science and Technology Beijing, Beijing 100083, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002945086","display_name":"Xinyu He","orcid":"https://orcid.org/0000-0003-1849-9949"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinyu He","raw_affiliation_strings":["School of Automation, University of Science and Technology Beijing, Beijing 100083, China"],"raw_orcid":"https://orcid.org/0000-0003-1849-9949","affiliations":[{"raw_affiliation_string":"School of Automation, University of Science and Technology Beijing, Beijing 100083, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027111642","display_name":"Zhengguang Xu","orcid":"https://orcid.org/0000-0002-3790-018X"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhengguang Xu","raw_affiliation_strings":["School of Automation, University of Science and Technology Beijing, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, University of Science and Technology Beijing, Beijing 100083, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100427815","display_name":"Lixin Zhang","orcid":"https://orcid.org/0000-0002-5338-1148"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Zhang","raw_affiliation_strings":["School of Automation, University of Science and Technology Beijing, Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, University of Science and Technology Beijing, Beijing 100083, China","institution_ids":["https://openalex.org/I92403157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002945086","https://openalex.org/A5027111642"],"corresponding_institution_ids":["https://openalex.org/I92403157"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":1.4729,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.84237898,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"12","issue":"6","first_page":"112","last_page":"112"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7032293081283569},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6794755458831787},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5881362557411194},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5794677734375},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5562451481819153},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5449960231781006},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5395833849906921},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5279768109321594},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5169314742088318},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.4544319808483124},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4279581308364868},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.42777928709983826},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4141996502876282},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.40286511182785034},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1962464153766632}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7032293081283569},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6794755458831787},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5881362557411194},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5794677734375},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5562451481819153},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5449960231781006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5395833849906921},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5279768109321594},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5169314742088318},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.4544319808483124},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4279581308364868},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.42777928709983826},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4141996502876282},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.40286511182785034},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1962464153766632}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/computers12060112","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers12060112","pdf_url":"https://www.mdpi.com/2073-431X/12/6/112/pdf?version=1685012758","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b4fad4570cec4178a834b9f4d3a77825","is_oa":true,"landing_page_url":"https://doaj.org/article/b4fad4570cec4178a834b9f4d3a77825","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":"Computers, Vol 12, Iss 6, p 112 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/computers12060112","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computers12060112","pdf_url":"https://www.mdpi.com/2073-431X/12/6/112/pdf?version=1685012758","source":{"id":"https://openalex.org/S4210228075","display_name":"Computers","issn_l":"2073-431X","issn":["2073-431X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4378231424.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1504755800","https://openalex.org/W1665214252","https://openalex.org/W1836465849","https://openalex.org/W1906770428","https://openalex.org/W1975992194","https://openalex.org/W2011181254","https://openalex.org/W2037642501","https://openalex.org/W2038596520","https://openalex.org/W2048695508","https://openalex.org/W2056370875","https://openalex.org/W2065301447","https://openalex.org/W2100556411","https://openalex.org/W2106224199","https://openalex.org/W2130975789","https://openalex.org/W2153663612","https://openalex.org/W2160547390","https://openalex.org/W2194775991","https://openalex.org/W2292560765","https://openalex.org/W2508457857","https://openalex.org/W2520164769","https://openalex.org/W2535891105","https://openalex.org/W2536599074","https://openalex.org/W2560809721","https://openalex.org/W2764207251","https://openalex.org/W2887194216","https://openalex.org/W2903629831","https://openalex.org/W2908554698","https://openalex.org/W2960060338","https://openalex.org/W2963725279","https://openalex.org/W2963774720","https://openalex.org/W2963783545","https://openalex.org/W2964116203","https://openalex.org/W2967098998","https://openalex.org/W2999111259","https://openalex.org/W3015520332","https://openalex.org/W3022574514","https://openalex.org/W3033835243","https://openalex.org/W3112965401","https://openalex.org/W3129492101","https://openalex.org/W3182000414","https://openalex.org/W3213635490","https://openalex.org/W4212784199","https://openalex.org/W4220999568","https://openalex.org/W4321497943","https://openalex.org/W6632305550","https://openalex.org/W6726381175"],"related_works":["https://openalex.org/W2953058328","https://openalex.org/W1542224353","https://openalex.org/W1661087619","https://openalex.org/W2750730210","https://openalex.org/W2116854923","https://openalex.org/W2555730586","https://openalex.org/W189037341","https://openalex.org/W1978749115","https://openalex.org/W2116498084","https://openalex.org/W2903565072"],"abstract_inverted_index":{"Noise":[0],"filtering":[1],"is":[2,61],"a":[3,105,136],"crucial":[4],"task":[5],"in":[6,88],"digital":[7],"image":[8,52,58,140],"processing,":[9],"performing":[10],"the":[11,35,57,92,95,114,118,123],"function":[12],"of":[13,37,56,67,85,94,117,125,139],"preprocessing.":[14],"In":[15],"this":[16],"paper,":[17],"we":[18],"propose":[19],"an":[20,64],"algorithm":[21,103],"that":[22,101],"employs":[23],"deep":[24],"convolution":[25,69],"and":[26,33,47,59,70,111,128],"soft":[27],"thresholding":[28],"iterative":[29],"algorithms":[30],"to":[31,82,90,132,135],"extract":[32],"learn":[34],"features":[36,42],"noisy":[38],"images.":[39,119],"The":[40,98],"extracted":[41],"are":[43],"acquired":[44],"through":[45],"prior":[46],"sparse":[48],"representation":[49],"theory":[50],"for":[51],"reconstruction.":[53],"Effective":[54],"separation":[55],"noise":[60],"achieved":[62,104],"using":[63],"end-to-end":[65],"network":[66],"dilated":[68],"fully":[71],"connected":[72],"layers.":[73],"Several":[74],"experiments":[75],"were":[76],"performed":[77],"on":[78],"public":[79],"images":[80],"subject":[81],"various":[83],"levels":[84],"Gaussian":[86],"noise,":[87],"order":[89],"evaluate":[91],"effectiveness":[93,124],"proposed":[96],"approach.":[97],"results":[99],"indicated":[100],"our":[102,126],"high":[106],"peak":[107],"signal-to-noise":[108],"ratio":[109],"(PSNR)":[110],"significantly":[112],"improved":[113],"visual":[115],"effects":[116],"Our":[120],"study":[121],"supports":[122],"approach":[127],"substantiates":[129],"its":[130],"potential":[131],"be":[133],"applied":[134],"broad":[137],"spectrum":[138],"processing":[141],"tasks.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-29T09:21:14.243279","created_date":"2025-10-10T00:00:00"}