{"id":"https://openalex.org/W2547245321","doi":"https://doi.org/10.1109/icacci.2016.7732314","title":"Removal of random-valued impulse noise using detection filters and group sparse modeling","display_name":"Removal of random-valued impulse noise using detection filters and group sparse modeling","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2547245321","doi":"https://doi.org/10.1109/icacci.2016.7732314","mag":"2547245321"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2016.7732314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732314","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5082519578","display_name":"Divya Velayudhan","orcid":"https://orcid.org/0000-0003-2897-570X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Divya Velayudhan","raw_affiliation_strings":["ECE Dept. S.C.T College of Engineering, Thiruvananthapuram, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECE Dept. S.C.T College of Engineering, Thiruvananthapuram, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067937234","display_name":"Salim Paul","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Salim Paul","raw_affiliation_strings":["ECE Dept. S.C.T College of Engineering, Thiruvananthapuram, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECE Dept. S.C.T College of Engineering, Thiruvananthapuram, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"1826","last_page":"1832"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9948999881744385,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9926999807357788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/impulse-noise","display_name":"Impulse noise","score":0.7596287727355957},{"id":"https://openalex.org/keywords/salt-and-pepper-noise","display_name":"Salt-and-pepper noise","score":0.6205037236213684},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5604124069213867},{"id":"https://openalex.org/keywords/randomness","display_name":"Randomness","score":0.5542892813682556},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5458124876022339},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5101521611213684},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47052252292633057},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.468219518661499},{"id":"https://openalex.org/keywords/impulse","display_name":"Impulse (physics)","score":0.4654195308685303},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.45473745465278625},{"id":"https://openalex.org/keywords/median-filter","display_name":"Median filter","score":0.4430449903011322},{"id":"https://openalex.org/keywords/inpainting","display_name":"Inpainting","score":0.4401014745235443},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.430738627910614},{"id":"https://openalex.org/keywords/image-noise","display_name":"Image noise","score":0.4213118553161621},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.402204304933548},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37065666913986206},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32751959562301636},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2875902056694031},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22519421577453613},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13910752534866333},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.07237699627876282}],"concepts":[{"id":"https://openalex.org/C127372701","wikidata":"https://www.wikidata.org/wiki/Q16979398","display_name":"Impulse noise","level":3,"score":0.7596287727355957},{"id":"https://openalex.org/C113660513","wikidata":"https://www.wikidata.org/wiki/Q849379","display_name":"Salt-and-pepper noise","level":5,"score":0.6205037236213684},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5604124069213867},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.5542892813682556},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5458124876022339},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5101521611213684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47052252292633057},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.468219518661499},{"id":"https://openalex.org/C70836080","wikidata":"https://www.wikidata.org/wiki/Q837940","display_name":"Impulse (physics)","level":2,"score":0.4654195308685303},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.45473745465278625},{"id":"https://openalex.org/C55352655","wikidata":"https://www.wikidata.org/wiki/Q304247","display_name":"Median filter","level":4,"score":0.4430449903011322},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.4401014745235443},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.430738627910614},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.4213118553161621},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.402204304933548},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37065666913986206},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32751959562301636},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2875902056694031},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22519421577453613},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13910752534866333},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.07237699627876282},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacci.2016.7732314","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732314","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W107968503","https://openalex.org/W1601202388","https://openalex.org/W1976709621","https://openalex.org/W2016732018","https://openalex.org/W2033603511","https://openalex.org/W2045737896","https://openalex.org/W2048015091","https://openalex.org/W2094903560","https://openalex.org/W2097073572","https://openalex.org/W2098900561","https://openalex.org/W2100249676","https://openalex.org/W2100315107","https://openalex.org/W2100705753","https://openalex.org/W2116013899","https://openalex.org/W2117865218","https://openalex.org/W2124139674","https://openalex.org/W2142058898","https://openalex.org/W2148358298","https://openalex.org/W2153663612","https://openalex.org/W2156600062","https://openalex.org/W2160817147","https://openalex.org/W2164893552","https://openalex.org/W2169733476","https://openalex.org/W2334911726","https://openalex.org/W2536599074","https://openalex.org/W3104720471","https://openalex.org/W4300710699","https://openalex.org/W6635761631"],"related_works":["https://openalex.org/W2953655071","https://openalex.org/W2121479027","https://openalex.org/W2082346846","https://openalex.org/W1978900443","https://openalex.org/W2415066633","https://openalex.org/W1787910866","https://openalex.org/W2545973440","https://openalex.org/W2518478289","https://openalex.org/W4285207306","https://openalex.org/W2083775566"],"abstract_inverted_index":{"High":[0],"quality":[1],"noise-free":[2],"images":[3,23,78],"constitute":[4],"an":[5],"integral":[6],"part":[7],"of":[8,22,29,73,77,144],"all":[9],"image":[10,119],"processing":[11],"applications.":[12],"Image":[13],"acquisition":[14],"and":[15,35,55,82],"transmission":[16],"stages":[17],"often":[18],"result":[19],"in":[20,60],"corruption":[21],"with":[24],"impulse":[25,68,89,108],"noise,":[26],"which":[27],"is":[28,44,58,132],"two":[30,40,74,93],"main":[31],"types:":[32],"salt-and-pepper":[33],"noise":[34,43,69,90],"random-valued":[36,42,67,88],"noise.":[37,109],"Among":[38],"the":[39,45,61,103,118,121,136,142,145],"types,":[41],"most":[46],"difficult":[47],"to":[48,52,134],"be":[49],"removed":[50],"due":[51],"its":[53],"randomness":[54],"this":[56],"problem":[57],"addressed":[59],"paper.":[62],"The":[63,85,95,110],"proposed":[64],"method":[65],"for":[66,87],"removal":[70,91],"takes":[71],"advantage":[72],"important":[75],"properties":[76],"\u2014":[79],"local":[80],"sparsity":[81],"non-local":[83],"self-similarity.":[84],"technique":[86],"has":[92],"stages.":[94],"first":[96],"stage":[97,101,112,116],"called":[98,113],"Impulse":[99],"Detection":[100],"identifies":[102],"outlier":[104],"candidates":[105],"affected":[106],"by":[107],"second":[111],"Inpainting-based":[114],"Reconstruction":[115],"reconstructs":[117],"from":[120],"unaffected":[122],"partial":[123],"random":[124],"samples.":[125],"A":[126],"robust":[127],"split":[128],"Bregman":[129],"iterative":[130],"algorithm":[131],"used":[133],"solve":[135],"optimization":[137],"problem.":[138],"Experimental":[139],"results":[140],"support":[141],"effectiveness":[143],"algorithm.":[146]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}