{"id":"https://openalex.org/W1868549062","doi":"https://doi.org/10.1109/tip.2015.2470599","title":"Dot-Diffused Halftoning With Improved Homogeneity","display_name":"Dot-Diffused Halftoning With Improved Homogeneity","publication_year":2015,"publication_date":"2015-08-24","ids":{"openalex":"https://openalex.org/W1868549062","doi":"https://doi.org/10.1109/tip.2015.2470599","mag":"1868549062","pmid":"https://pubmed.ncbi.nlm.nih.gov/26316124"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2015.2470599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2015.2470599","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1508.05373","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yun-Fu Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Yun-Fu Liu","raw_affiliation_strings":["Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jing-Ming Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jing-Ming Guo","raw_affiliation_strings":["Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I154864474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154864474"],"apc_list":null,"apc_paid":null,"fwci":0.8793,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.74603572,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"24","issue":"11","first_page":"4581","last_page":"4591"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11666","display_name":"Color Science and Applications","score":0.9670000076293945,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11666","display_name":"Color Science and Applications","score":0.9670000076293945,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11338","display_name":"Advancements in Photolithography Techniques","score":0.002899999963119626,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.0026000000070780516,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/halftone","display_name":"Halftone","score":0.925000011920929},{"id":"https://openalex.org/keywords/dither","display_name":"Dither","score":0.8105000257492065},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5810999870300293},{"id":"https://openalex.org/keywords/homogeneity","display_name":"Homogeneity (statistics)","score":0.5511999726295471},{"id":"https://openalex.org/keywords/crts","display_name":"CRTS","score":0.4803999960422516},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.44830000400543213},{"id":"https://openalex.org/keywords/colors-of-noise","display_name":"Colors of noise","score":0.44339999556541443},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4429999887943268},{"id":"https://openalex.org/keywords/alias","display_name":"Alias","score":0.4309999942779541},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.42329999804496765}],"concepts":[{"id":"https://openalex.org/C2777635815","wikidata":"https://www.wikidata.org/wiki/Q1110021","display_name":"Halftone","level":3,"score":0.925000011920929},{"id":"https://openalex.org/C70451592","wikidata":"https://www.wikidata.org/wiki/Q376493","display_name":"Dither","level":3,"score":0.8105000257492065},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5810999870300293},{"id":"https://openalex.org/C142259097","wikidata":"https://www.wikidata.org/wiki/Q5891314","display_name":"Homogeneity (statistics)","level":2,"score":0.5511999726295471},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5291000008583069},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4805999994277954},{"id":"https://openalex.org/C2777521450","wikidata":"https://www.wikidata.org/wiki/Q43171778","display_name":"CRTS","level":2,"score":0.4803999960422516},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47999998927116394},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.44830000400543213},{"id":"https://openalex.org/C114996537","wikidata":"https://www.wikidata.org/wiki/Q4854529","display_name":"Colors of noise","level":3,"score":0.44339999556541443},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4429999887943268},{"id":"https://openalex.org/C46681722","wikidata":"https://www.wikidata.org/wiki/Q4725589","display_name":"Alias","level":2,"score":0.4309999942779541},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.42329999804496765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4074999988079071},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4066999852657318},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4066999852657318},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.4018999934196472},{"id":"https://openalex.org/C9083635","wikidata":"https://www.wikidata.org/wiki/Q2133535","display_name":"Noise shaping","level":2,"score":0.38670000433921814},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3767000138759613},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C203234222","wikidata":"https://www.wikidata.org/wiki/Q2133519","display_name":"Noise power","level":3,"score":0.2913999855518341},{"id":"https://openalex.org/C42781572","wikidata":"https://www.wikidata.org/wiki/Q1250322","display_name":"Digital image","level":4,"score":0.2906000018119812},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.289900004863739},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.26899999380111694},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.2581999897956848},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C2778307483","wikidata":"https://www.wikidata.org/wiki/Q5149038","display_name":"Colored","level":2,"score":0.2535000145435333},{"id":"https://openalex.org/C105344744","wikidata":"https://www.wikidata.org/wiki/Q958957","display_name":"Spread spectrum","level":3,"score":0.2513999938964844}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2015.2470599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2015.2470599","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:26316124","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26316124","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:arXiv.org:1508.05373","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1508.05373","pdf_url":"https://arxiv.org/pdf/1508.05373","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1508.05373","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1508.05373","pdf_url":"https://arxiv.org/pdf/1508.05373","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1979449170","https://openalex.org/W2000014233","https://openalex.org/W2006045909","https://openalex.org/W2014038925","https://openalex.org/W2053717006","https://openalex.org/W2076201900","https://openalex.org/W2094050030","https://openalex.org/W2099662762","https://openalex.org/W2106822551","https://openalex.org/W2111870029","https://openalex.org/W2114504939","https://openalex.org/W2129182781","https://openalex.org/W2131062190","https://openalex.org/W2144085591","https://openalex.org/W2155351485","https://openalex.org/W2159978942","https://openalex.org/W2170293516","https://openalex.org/W2170296230","https://openalex.org/W2171677391","https://openalex.org/W3005381663","https://openalex.org/W4232416900","https://openalex.org/W4236789552","https://openalex.org/W6642724331","https://openalex.org/W6644675044"],"related_works":[],"abstract_inverted_index":{"Compared":[0],"with":[1,105],"the":[2,27,39,49,52,56,66,78,87,91,98,110,118,135],"error":[3],"diffusion,":[4],"dot":[5,112],"diffusion":[6,113],"provides":[7],"an":[8,61],"additional":[9],"pixel-level":[10],"parallelism":[11],"for":[12],"digital":[13],"halftoning.":[14],"However,":[15],"even":[16],"though":[17],"its":[18],"periodic":[19],"and":[20,65,128,131],"blocking":[21],"artifacts":[22],"had":[23],"been":[24],"eased":[25],"by":[26,60],"previous":[28],"works,":[29],"it":[30],"was":[31],"still":[32],"far":[33],"from":[34],"satisfactory":[35],"in":[36,123],"terms":[37,124],"of":[38,55,76,90,101,125],"blue":[40],"noise":[41],"spectrum":[42,81],"perspective.":[43],"In":[44],"this":[45],"paper,":[46],"we":[47],"strengthen":[48],"relation":[50],"among":[51],"pixel":[53],"locations":[54],"same":[57],"processing":[58],"order":[59],"iterative":[62],"halftoning":[63,103,121],"method,":[64],"results":[67],"demonstrate":[68],"a":[69,73,108],"significant":[70],"improvement.":[71],"Moreover,":[72],"new":[74],"approach":[75],"deriving":[77],"averaged":[79],"power":[80],"density":[82],"is":[83,114,140],"proposed":[84,111],"to":[85,117,134],"avoid":[86],"regular":[88],"sampling":[89],"well-known":[92],"Bartlett's":[93],"procedure":[94],"which":[95],"inaccurately":[96],"presents":[97],"halftone":[99],"periodicity":[100],"certain":[102],"techniques":[104],"parallelism.":[106],"As":[107],"result,":[109],"substantially":[115],"superior":[116],"state-of-the-art":[119],"parallel":[120],"methods":[122],"visual":[126],"quality":[127],"artifact-free":[129],"property,":[130],"competitive":[132],"runtime":[133],"theoretical":[136],"fastest":[137],"ordered":[138],"dithering":[139],"offered":[141],"simultaneously.":[142]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2016-06-24T00:00:00"}
