{"id":"https://openalex.org/W2908150373","doi":"https://doi.org/10.1109/icapr.2017.8593110","title":"Non-local Gradient Fidelity Model for Multiplicative Gamma Noise Removal","display_name":"Non-local Gradient Fidelity Model for Multiplicative Gamma Noise Removal","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2908150373","doi":"https://doi.org/10.1109/icapr.2017.8593110","mag":"2908150373"},"language":"en","primary_location":{"id":"doi:10.1109/icapr.2017.8593110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icapr.2017.8593110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR)","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":null,"display_name":"B. Balaji","orcid":null},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"B. Balaji","raw_affiliation_strings":["Department of Mathematical and Computational Sciences, National Institute of Technology Karnataka, Mangalore"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical and Computational Sciences, National Institute of Technology Karnataka, Mangalore","institution_ids":["https://openalex.org/I11880225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020693411","display_name":"P. Jidesh","orcid":null},"institutions":[{"id":"https://openalex.org/I11880225","display_name":"National Institute of Technology Karnataka","ror":"https://ror.org/01hz4v948","country_code":"IN","type":"education","lineage":["https://openalex.org/I11880225"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"P. Jidesh","raw_affiliation_strings":["Department of Mathematical and Computational Sciences, National Institute of Technology Karnataka, Mangalore"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical and Computational Sciences, National Institute of Technology Karnataka, Mangalore","institution_ids":["https://openalex.org/I11880225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I11880225"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.26126092,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"5","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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9976999759674072,"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":0.9976999759674072,"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/multiplicative-noise","display_name":"Multiplicative noise","score":0.6407605409622192},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6130107641220093},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.6072556376457214},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5890387296676636},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.5653315782546997},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5177487730979919},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5011856555938721},{"id":"https://openalex.org/keywords/balanced-flow","display_name":"Balanced flow","score":0.497224360704422},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.48642683029174805},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.4805172383785248},{"id":"https://openalex.org/keywords/anisotropic-diffusion","display_name":"Anisotropic diffusion","score":0.4717729091644287},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4486874043941498},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4463717043399811},{"id":"https://openalex.org/keywords/vector-field","display_name":"Vector field","score":0.43907594680786133},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.4343040883541107},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42401134967803955},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4190177321434021},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.4138336181640625},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3495216965675354},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2775041460990906},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11227783560752869},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.1064368486404419},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.0882197916507721}],"concepts":[{"id":"https://openalex.org/C18015164","wikidata":"https://www.wikidata.org/wiki/Q6935000","display_name":"Multiplicative noise","level":5,"score":0.6407605409622192},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6130107641220093},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.6072556376457214},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5890387296676636},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.5653315782546997},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5177487730979919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5011856555938721},{"id":"https://openalex.org/C167879884","wikidata":"https://www.wikidata.org/wiki/Q727568","display_name":"Balanced flow","level":2,"score":0.497224360704422},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.48642683029174805},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.4805172383785248},{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.4717729091644287},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4486874043941498},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4463717043399811},{"id":"https://openalex.org/C91188154","wikidata":"https://www.wikidata.org/wiki/Q186247","display_name":"Vector field","level":2,"score":0.43907594680786133},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.4343040883541107},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42401134967803955},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4190177321434021},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.4138336181640625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3495216965675354},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2775041460990906},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11227783560752869},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1064368486404419},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0882197916507721},{"id":"https://openalex.org/C13412647","wikidata":"https://www.wikidata.org/wiki/Q174948","display_name":"Analog signal","level":3,"score":0.0},{"id":"https://openalex.org/C131021393","wikidata":"https://www.wikidata.org/wiki/Q7512759","display_name":"Signal transfer function","level":4,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icapr.2017.8593110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icapr.2017.8593110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Ninth International Conference on Advances in Pattern Recognition (ICAPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1536200267","https://openalex.org/W1971931849","https://openalex.org/W1980516668","https://openalex.org/W1995328941","https://openalex.org/W1998339281","https://openalex.org/W1999750309","https://openalex.org/W2004928853","https://openalex.org/W2049909233","https://openalex.org/W2056546164","https://openalex.org/W2060945009","https://openalex.org/W2069871306","https://openalex.org/W2092663520","https://openalex.org/W2097073572","https://openalex.org/W2103559027","https://openalex.org/W2104763670","https://openalex.org/W2110264793","https://openalex.org/W2118324237","https://openalex.org/W2130094715","https://openalex.org/W2133665775","https://openalex.org/W2142058898","https://openalex.org/W2150134853","https://openalex.org/W2160752412","https://openalex.org/W2169899245","https://openalex.org/W2254645249","https://openalex.org/W2316506203","https://openalex.org/W2475792673","https://openalex.org/W6631983884","https://openalex.org/W6673594753","https://openalex.org/W6691773039","https://openalex.org/W6912511727"],"related_works":["https://openalex.org/W2366558118","https://openalex.org/W2393426979","https://openalex.org/W2159155702","https://openalex.org/W1999581389","https://openalex.org/W1859619809","https://openalex.org/W2348246732","https://openalex.org/W2944181031","https://openalex.org/W1999448661","https://openalex.org/W1976248695","https://openalex.org/W1969304600"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"a":[3],"non-local":[4,45],"gradient":[5,60],"vector":[6],"flow":[7],"model":[8,68],"is":[9,55,69],"designed":[10],"for":[11,72,92],"restoration":[12,73],"of":[13,36,43,74,80],"images":[14,76],"corrupted":[15],"with":[16],"Gamma":[17],"distributed":[18],"(speckle)":[19],"noise":[20],"and":[21,30,50,82,90,99],"linear":[22,53],"blurring":[23],"artefacts.":[24],"The":[25,67,85],"filter":[26],"effectively":[27],"preserves":[28],"edges":[29],"finer":[31],"details":[32],"in":[33,64],"the":[34,41,44,51,59,65,78],"course":[35],"its":[37],"evolution":[38],"due":[39],"to":[40],"presence":[42],"TV":[46],"based":[47],"diffusion":[48],"term":[49,62],"piecewise":[52],"approximation":[54],"reduced":[56],"considerably":[57],"by":[58],"fidelity":[61],"present":[63],"model.":[66],"found":[70],"suitable":[71],"various":[75,102],"from":[77],"field":[79],"satellite":[81],"clinical":[83],"imaging.":[84],"experimental":[86],"results":[87],"are":[88],"shown":[89],"compared":[91],"different":[93],"image":[94],"data":[95],"sets":[96],"both":[97],"visually":[98],"qualitatively":[100],"using":[101],"statistical":[103],"measures.":[104]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}
