{"id":"https://openalex.org/W2507511309","doi":"https://doi.org/10.1145/2905055.2905104","title":"An Alternative Framework of Anisotropic Diffusion for Image Denoising","display_name":"An Alternative Framework of Anisotropic Diffusion for Image Denoising","publication_year":2016,"publication_date":"2016-03-04","ids":{"openalex":"https://openalex.org/W2507511309","doi":"https://doi.org/10.1145/2905055.2905104","mag":"2507511309"},"language":"en","primary_location":{"id":"doi:10.1145/2905055.2905104","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2905055.2905104","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies","raw_type":"proceedings-article"},"type":"article","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/A5077398759","display_name":"Subit K. Jain","orcid":"https://orcid.org/0000-0001-8137-4415"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Subit K. Jain","raw_affiliation_strings":["School of Basic Sceince, Indian Institute Technology Mandi, Himanchal, India"],"affiliations":[{"raw_affiliation_string":"School of Basic Sceince, Indian Institute Technology Mandi, Himanchal, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103201709","display_name":"Rajendra K. Ray","orcid":"https://orcid.org/0000-0003-2283-3778"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajendra K. Ray","raw_affiliation_strings":["School of Basic Sceince, Indian Institute Technology Mandi, Himanchal, India"],"affiliations":[{"raw_affiliation_string":"School of Basic Sceince, Indian Institute Technology Mandi, Himanchal, India","institution_ids":["https://openalex.org/I9579091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5077398759"],"corresponding_institution_ids":["https://openalex.org/I9579091"],"apc_list":null,"apc_paid":null,"fwci":0.501,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72170104,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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":0.9998000264167786,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9979000091552734,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.989799976348877,"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/anisotropic-diffusion","display_name":"Anisotropic diffusion","score":0.8055638074874878},{"id":"https://openalex.org/keywords/sigmoid-function","display_name":"Sigmoid function","score":0.654096782207489},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6433342695236206},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6178076863288879},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.602210521697998},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5827533006668091},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.5720061659812927},{"id":"https://openalex.org/keywords/edge-preserving-smoothing","display_name":"Edge-preserving smoothing","score":0.5708129405975342},{"id":"https://openalex.org/keywords/tangent","display_name":"Tangent","score":0.5371926426887512},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4811869263648987},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47459977865219116},{"id":"https://openalex.org/keywords/structure-tensor","display_name":"Structure tensor","score":0.4691770374774933},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.465948224067688},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.43121692538261414},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43054622411727905},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4225218594074249},{"id":"https://openalex.org/keywords/image-noise","display_name":"Image noise","score":0.414200097322464},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39984962344169617},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31902486085891724},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0840599536895752},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.06914496421813965},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.06775295734405518}],"concepts":[{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.8055638074874878},{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.654096782207489},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6433342695236206},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6178076863288879},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.602210521697998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5827533006668091},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.5720061659812927},{"id":"https://openalex.org/C141651230","wikidata":"https://www.wikidata.org/wiki/Q5337637","display_name":"Edge-preserving smoothing","level":4,"score":0.5708129405975342},{"id":"https://openalex.org/C138187205","wikidata":"https://www.wikidata.org/wiki/Q131251","display_name":"Tangent","level":2,"score":0.5371926426887512},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4811869263648987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47459977865219116},{"id":"https://openalex.org/C113315163","wikidata":"https://www.wikidata.org/wiki/Q7625159","display_name":"Structure tensor","level":3,"score":0.4691770374774933},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.465948224067688},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.43121692538261414},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43054622411727905},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4225218594074249},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.414200097322464},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39984962344169617},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31902486085891724},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0840599536895752},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.06914496421813965},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.06775295734405518},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2905055.2905104","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2905055.2905104","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W270188234","https://openalex.org/W1256797459","https://openalex.org/W1480546554","https://openalex.org/W1963743024","https://openalex.org/W2003342624","https://openalex.org/W2031837444","https://openalex.org/W2065164181","https://openalex.org/W2103559027","https://openalex.org/W2116609734","https://openalex.org/W2133155955","https://openalex.org/W2146052399","https://openalex.org/W2150134853","https://openalex.org/W2151958211","https://openalex.org/W2164507445","https://openalex.org/W2165015795","https://openalex.org/W2229600047","https://openalex.org/W2498216762","https://openalex.org/W2536640702","https://openalex.org/W2629881577","https://openalex.org/W3011612142","https://openalex.org/W3023411394","https://openalex.org/W7027716524"],"related_works":["https://openalex.org/W2581436517","https://openalex.org/W2262332166","https://openalex.org/W2373529328","https://openalex.org/W1966786995","https://openalex.org/W2154534640","https://openalex.org/W2068096977","https://openalex.org/W2357692229","https://openalex.org/W2055952631","https://openalex.org/W2612809596","https://openalex.org/W1964941127"],"abstract_inverted_index":{"This":[0],"paper":[1],"deals":[2],"with":[3],"an":[4],"anisotropic":[5],"diffusion":[6,15],"based":[7,17,27],"noise":[8,42,88],"removal":[9],"technique":[10],"which":[11,83],"utilizes":[12],"the":[13,36,41,51,57,65,93],"new":[14],"function":[16,26],"on":[18,28,80],"tangent":[19],"sigmoid":[20],"function.":[21],"A":[22],"local":[23,29],"edge":[24],"indicator":[25],"structure":[30],"tensor":[31],"is":[32,60,96],"also":[33],"used":[34],"in":[35,47,69],"proposed":[37,58,94],"technique,":[38],"to":[39,64],"reduce":[40],"and":[43,62,74,89],"detection":[44],"of":[45,71],"edges":[46],"digital":[48],"images.":[49],"From":[50],"experimental":[52],"results,":[53],"we":[54],"observe":[55],"that":[56,92],"method":[59],"better":[61],"near":[63],"other":[66],"state-of-the-art":[67],"approaches,":[68],"terms":[70],"both":[72],"qualitatively":[73],"quantitatively.":[75],"Numerical":[76],"tests":[77],"were":[78],"performed":[79],"various":[81],"images,":[82],"are":[84],"corrupted":[85],"by":[86],"Gaussian":[87],"results":[90],"illustrate":[91],"approach":[95],"more":[97],"efficient":[98],"than":[99],"existing":[100],"one.":[101]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
