{"id":"https://openalex.org/W4308234329","doi":"https://doi.org/10.1109/icip46576.2022.9897678","title":"Practical Bulk Denoising Of Large Binary Images","display_name":"Practical Bulk Denoising Of Large Binary Images","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308234329","doi":"https://doi.org/10.1109/icip46576.2022.9897678"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897678","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","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":"Ignacio Ramirez Paulino","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ignacio Ramirez Paulino","raw_affiliation_strings":["Instituto De Ingeniería Eléctrica,Universidad De La República,Montevideo,Uruguay"],"affiliations":[{"raw_affiliation_string":"Instituto De Ingeniería Eléctrica,Universidad De La República,Montevideo,Uruguay","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10558433,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"196","last_page":"200"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9973000288009644,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9962000250816345,"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/benchmark","display_name":"Benchmark (surveying)","score":0.7693696022033691},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.7458550930023193},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6996762156486511},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6707030534744263},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.6418411731719971},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.6270633339881897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5723836421966553},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46753451228141785},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.43238285183906555},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4010915756225586},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3349766135215759},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2304973006248474}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7693696022033691},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.7458550930023193},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6996762156486511},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6707030534744263},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.6418411731719971},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.6270633339881897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5723836421966553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46753451228141785},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.43238285183906555},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4010915756225586},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3349766135215759},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2304973006248474},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip46576.2022.9897678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897678","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","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":16,"referenced_works":["https://openalex.org/W1527465884","https://openalex.org/W1997148185","https://openalex.org/W2047710600","https://openalex.org/W2058005980","https://openalex.org/W2076355923","https://openalex.org/W2097073572","https://openalex.org/W2144138356","https://openalex.org/W2163292085","https://openalex.org/W2172275395","https://openalex.org/W2345181424","https://openalex.org/W2906893282","https://openalex.org/W4241028811","https://openalex.org/W4292003313","https://openalex.org/W4294224090","https://openalex.org/W6712275366","https://openalex.org/W6794521276"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175"],"abstract_inverted_index":{"This":[0],"paper":[1],"explores":[2],"the":[3,28,40,47,81,98,104,117,123],"problem":[4],"of":[5,14,35,46],"removing":[6],"real,":[7],"non-simulated":[8],"noise":[9,75],"from":[10],"a":[11,32,77,112],"large":[12,15],"body":[13],"binary":[16,53],"images.":[17,84],"Three":[18],"denoising":[19],"methods":[20,67,87],"are":[21,68,109],"evaluated":[22],"for":[23,52],"their":[24],"efficacy":[25],"and":[26,43,70,79,130,132],"speed:":[27],"well":[29],"known":[30,64],"DUDE,":[31],"novel":[33],"variant":[34],"it":[36],"which":[37],"we":[38],"call":[39],"Quorum":[41,118],"Denoiser,":[42],"an":[44],"adaptation":[45],"Non-Local":[48],"Means":[49],"(NLM)":[50],"method":[51],"images,":[54],"B-NLM":[55,99],"which,":[56],"to":[57,111,121],"our":[58],"knowledge,":[59],"is":[60,100],"faster":[61],"than":[62,103],"other":[63,105],"variants.":[65],"The":[66],"compared":[69],"tested":[71],"both":[72,126],"on":[73,80,91],"simulated":[74],"(as":[76],"benchmark)":[78],"real":[82,92],"life":[83],"All":[85],"three":[86],"produce":[88],"good":[89],"results":[90],"noise.":[93],"However,":[94],"despite":[95],"being":[96],"optimized,":[97],"significantly":[101],"slower":[102],"two,":[106],"whose":[107],"speeds":[108],"comparable":[110],"plain":[113],"median":[114],"filter.":[115],"Overall,":[116],"denoiser":[119],"appears":[120],"be":[122],"best":[124],"option,":[125],"in":[127],"quality":[128],"(real":[129],"simulated)":[131],"speed.":[133]},"counts_by_year":[],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}