{"id":"https://openalex.org/W2963495716","doi":"https://doi.org/10.1109/icassp.2018.8461388","title":"Group Sparsity Residual with Non-Local Samples for Image Denoising","display_name":"Group Sparsity Residual with Non-Local Samples for Image Denoising","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2963495716","doi":"https://doi.org/10.1109/icassp.2018.8461388","mag":"2963495716"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2018.8461388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8461388","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5032774989","display_name":"Zhiyuan Zha","orcid":"https://orcid.org/0000-0002-5515-5339"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Zha","raw_affiliation_strings":["School of Electronic Science and Engineering, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Science and Engineering, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089320702","display_name":"Xinggan Zhang","orcid":"https://orcid.org/0000-0002-4181-580X"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinggan Zhang","raw_affiliation_strings":["School of Electronic Science and Engineering, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Science and Engineering, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100417387","display_name":"Qiong Wang","orcid":"https://orcid.org/0000-0002-8183-8168"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiong Wang","raw_affiliation_strings":["School of Electronic Science and Engineering, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Science and Engineering, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022964450","display_name":"Yechao Bai","orcid":"https://orcid.org/0000-0001-5244-674X"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yechao Bai","raw_affiliation_strings":["School of Electronic Science and Engineering, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Science and Engineering, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041083348","display_name":"Lan Tang","orcid":"https://orcid.org/0000-0002-1646-8455"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lan Tang","raw_affiliation_strings":["School of Electronic Science and Engineering, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Science and Engineering, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015431603","display_name":"Xin Yuan","orcid":"https://orcid.org/0000-0002-8311-7524"},"institutions":[{"id":"https://openalex.org/I72090969","display_name":"Nokia (United States)","ror":"https://ror.org/038km2573","country_code":"US","type":"company","lineage":["https://openalex.org/I2738502077","https://openalex.org/I72090969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Yuan","raw_affiliation_strings":["Nokia Bell Labs, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nokia Bell Labs, NJ, USA","institution_ids":["https://openalex.org/I72090969"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1353","last_page":"1357"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9997000098228455,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9976999759674072,"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/residual","display_name":"Residual","score":0.8150203227996826},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5529192686080933},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5145137310028076},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5134876370429993},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4977438747882843},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49624162912368774},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48473140597343445},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.48385536670684814},{"id":"https://openalex.org/keywords/shrinkage","display_name":"Shrinkage","score":0.457061231136322},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.4495377540588379},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4336298704147339},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3321758508682251},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11296871304512024}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8150203227996826},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5529192686080933},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5145137310028076},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5134876370429993},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4977438747882843},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49624162912368774},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48473140597343445},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.48385536670684814},{"id":"https://openalex.org/C180145272","wikidata":"https://www.wikidata.org/wiki/Q7504144","display_name":"Shrinkage","level":2,"score":0.457061231136322},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.4495377540588379},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4336298704147339},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3321758508682251},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11296871304512024}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2018.8461388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8461388","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1607704809","https://openalex.org/W1906770428","https://openalex.org/W1915372217","https://openalex.org/W1963932623","https://openalex.org/W1978749115","https://openalex.org/W1985894000","https://openalex.org/W2011181254","https://openalex.org/W2014311222","https://openalex.org/W2045737896","https://openalex.org/W2048695508","https://openalex.org/W2056370875","https://openalex.org/W2075157914","https://openalex.org/W2085692415","https://openalex.org/W2097073572","https://openalex.org/W2103559027","https://openalex.org/W2111557737","https://openalex.org/W2113945798","https://openalex.org/W2115706991","https://openalex.org/W2116857329","https://openalex.org/W2117865218","https://openalex.org/W2125527601","https://openalex.org/W2136396015","https://openalex.org/W2153663612","https://openalex.org/W2156242833","https://openalex.org/W2160547390","https://openalex.org/W2172275395","https://openalex.org/W2207282238","https://openalex.org/W2289219634","https://openalex.org/W2295281957","https://openalex.org/W2508457857","https://openalex.org/W2513228454","https://openalex.org/W2536599074","https://openalex.org/W2585690249","https://openalex.org/W2641816967","https://openalex.org/W2779105280","https://openalex.org/W2963129783","https://openalex.org/W2963689682","https://openalex.org/W3099794995","https://openalex.org/W6640074720","https://openalex.org/W6674723063","https://openalex.org/W6685348629","https://openalex.org/W6726536556","https://openalex.org/W6728784816","https://openalex.org/W6730103001","https://openalex.org/W6733160403","https://openalex.org/W6739819438"],"related_works":["https://openalex.org/W2391958761","https://openalex.org/W2765453142","https://openalex.org/W2356780078","https://openalex.org/W2356008845","https://openalex.org/W255134961","https://openalex.org/W2348314720","https://openalex.org/W2243547089","https://openalex.org/W2316482937","https://openalex.org/W2910550880","https://openalex.org/W2126683262"],"abstract_inverted_index":{"Inspired":[0],"by":[1,29,108,119],"group-based":[2,36],"sparse":[3,37,106],"coding,":[4],"recently":[5],"proposed":[6,130],"group":[7,105],"sparsity":[8],"residual":[9,28],"(GSR)":[10],"scheme":[11],"has":[12],"demonstrated":[13],"superior":[14],"performance":[15],"in":[16,22,85],"image":[17,90,110],"processing.":[18],"However,":[19],"one":[20],"challenge":[21],"GSR":[23,87,117],"is":[24,41],"to":[25,43,47,77],"estimate":[26],"the":[27,35,48,55,79,86,104,109,116,129,141],"using":[30],"a":[31,100],"proper":[32],"reference":[33,84],"of":[34,103,144],"coding":[38],"(GSC),":[39],"which":[40,64],"desired":[42],"be":[44],"as":[45,50,83],"close":[46],"truth":[49],"possible.":[51],"Previous":[52],"researches":[53],"utilized":[54],"estimations":[56],"from":[57],"other":[58],"algorithms":[59],"(i.e.,":[60],"GMM":[61],"or":[62,69],"BM3D),":[63],"are":[65],"either":[66],"not":[67,132],"accurate":[68],"too":[70],"slow.":[71],"In":[72],"this":[73],"paper,":[74],"we":[75,97],"propose":[76],"use":[78],"Non-Local":[80],"Samples":[81],"(NL-S)":[82],"regime":[88],"for":[89],"denoising,":[91],"thus":[92],"termed":[93],"GSR-NLS.":[94],"More":[95],"specifically,":[96],"first":[98],"obtain":[99],"good":[101],"estimation":[102],"coefficients":[107],"nonlocal":[111],"self-similarity,":[112],"and":[113],"then":[114],"solve":[115],"model":[118],"an":[120],"effective":[121],"iterative":[122],"shrinkage":[123],"algorithm.":[124],"Experimental":[125],"results":[126],"demonstrate":[127],"that":[128],"GSR-NLS":[131],"only":[133],"outperforms":[134],"many":[135],"state-of-the-art":[136],"methods,":[137],"but":[138],"also":[139],"delivers":[140],"competitive":[142],"advantage":[143],"speed.":[145]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}