{"id":"https://openalex.org/W2135258870","doi":"https://doi.org/10.1109/icip.2004.1418752","title":"Joint blind separation and restoration of mixed degraded images for document analysis","display_name":"Joint blind separation and restoration of mixed degraded images for document analysis","publication_year":2005,"publication_date":"2005-04-19","ids":{"openalex":"https://openalex.org/W2135258870","doi":"https://doi.org/10.1109/icip.2004.1418752","mag":"2135258870"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2004.1418752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2004.1418752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 International Conference on Image Processing, 2004. ICIP '04.","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/A5048164151","display_name":"Anna Tonazzini","orcid":"https://orcid.org/0000-0001-6970-4725"},"institutions":[{"id":"https://openalex.org/I122991210","display_name":"Istituto di Scienza e Tecnologie dell'Informazione \"Alessandro Faedo\"","ror":"https://ror.org/05kacka20","country_code":"IT","type":"facility","lineage":["https://openalex.org/I122991210","https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"A. Tonazzini","raw_affiliation_strings":["Istituto di Scienza e Tecnologie dell'Informazione, Consiglio Nazionale delle Ricerche, Pisa, Italy"],"affiliations":[{"raw_affiliation_string":"Istituto di Scienza e Tecnologie dell'Informazione, Consiglio Nazionale delle Ricerche, Pisa, Italy","institution_ids":["https://openalex.org/I122991210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085223938","display_name":"Ivan Gerace","orcid":"https://orcid.org/0000-0003-1430-1712"},"institutions":[{"id":"https://openalex.org/I27483092","display_name":"University of Perugia","ror":"https://ror.org/00x27da85","country_code":"IT","type":"education","lineage":["https://openalex.org/I27483092"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"I. Gerace","raw_affiliation_strings":["Dipartimento di Matematica e Informatica, Universit\u00e0 degli Studi di Perugia, Perugia, Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Matematica e Informatica, Universit\u00e0 degli Studi di Perugia, Perugia, Italy","institution_ids":["https://openalex.org/I27483092"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017261181","display_name":"Francesco Cricco","orcid":null},"institutions":[{"id":"https://openalex.org/I27483092","display_name":"University of Perugia","ror":"https://ror.org/00x27da85","country_code":"IT","type":"education","lineage":["https://openalex.org/I27483092"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"F. Cricco","raw_affiliation_strings":["Dipartimento di Matematica e Informatica, Universit\u00e0 degli Studi di Perugia, Perugia, Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Matematica e Informatica, Universit\u00e0 degli Studi di Perugia, Perugia, Italy","institution_ids":["https://openalex.org/I27483092"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048164151"],"corresponding_institution_ids":["https://openalex.org/I122991210"],"apc_list":null,"apc_paid":null,"fwci":0.6359,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.70378964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"311","last_page":"314"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9854999780654907,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9833999872207642,"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/deblurring","display_name":"Deblurring","score":0.9027103185653687},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.7439095973968506},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6742291450500488},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.6735278964042664},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.671588122844696},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.6435598731040955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6258388161659241},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.5297133922576904},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5257241129875183},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42703476548194885},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4242743253707886},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40503984689712524},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3308057487010956},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.10622662305831909}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.9027103185653687},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.7439095973968506},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6742291450500488},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.6735278964042664},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.671588122844696},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.6435598731040955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6258388161659241},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.5297133922576904},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5257241129875183},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42703476548194885},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4242743253707886},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40503984689712524},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3308057487010956},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.10622662305831909},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2004.1418752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2004.1418752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 International Conference on Image Processing, 2004. ICIP '04.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W73692885","https://openalex.org/W201194781","https://openalex.org/W2035508962","https://openalex.org/W2038290463","https://openalex.org/W2052486024","https://openalex.org/W2105909330","https://openalex.org/W2126016605","https://openalex.org/W2141224535","https://openalex.org/W2167925415","https://openalex.org/W2170709565","https://openalex.org/W2171218400","https://openalex.org/W6603088516","https://openalex.org/W6608194230"],"related_works":["https://openalex.org/W2390344110","https://openalex.org/W2046761971","https://openalex.org/W2364896863","https://openalex.org/W2361066326","https://openalex.org/W2182042810","https://openalex.org/W2130656060","https://openalex.org/W2156932837","https://openalex.org/W2380698615","https://openalex.org/W2031788393","https://openalex.org/W374502268"],"abstract_inverted_index":{"We":[0,34,107],"consider":[1],"the":[2,54,62,66,74,77,83,97,101,105,113,122],"problem":[3],"of":[4,11,20,50,65,85,100,137],"extracting":[5],"clean":[6],"images":[7,12,29,79],"from":[8],"noisy":[9],"mixtures":[10],"degraded":[13],"by":[14,42],"blur":[15,114],"operators.":[16],"This":[17],"special":[18],"case":[19],"source":[21,45],"separation":[22,46,123],"arises,":[23],"for":[24,96],"instance,":[25],"when":[26],"analyzing":[27],"document":[28],"showing":[30],"bleed-through":[31,140],"or":[32],"show-through.":[33],"propose":[35],"to":[36,149],"jointly":[37],"perform":[38],"demixing":[39],"and":[40,90,104,116,125],"deblurring":[41],"augmenting":[43],"blind":[44],"with":[47],"a":[48,70,91,117],"step":[49],"image":[51,119],"restoration.":[52],"Within":[53],"independent":[55],"component":[56],"analysis":[57],"(ICA)":[58],"approach,":[59],"i.e.":[60],"assuming":[61],"statistical":[63],"independence":[64],"sources,":[67],"we":[68],"adopt":[69],"Bayesian":[71],"formulation":[72],"where":[73],"priors":[75,145],"on":[76,134],"ideal":[78],"are":[80,141,147],"given":[81],"in":[82],"form":[84],"Markov":[86],"random":[87],"field":[88],"(MRF),":[89],"MAP":[92],"estimation":[93],"is":[94],"employed":[95],"joint":[98],"recovery":[99],"mixing":[102],"matrix":[103],"images.":[106,152],"show":[108],"that":[109,146],"taking":[110],"into":[111],"account":[112],"model":[115,120],"proper":[118],"improves":[121],"process":[124],"makes":[126],"it":[127],"more":[128],"robust":[129],"against":[130],"noise.":[131],"Preliminary":[132],"results":[133],"synthetic":[135],"examples":[136],"documents":[138],"exhibiting":[139],"provided,":[142],"considering":[143],"edge-preserving":[144],"suitable":[148],"describe":[150],"text":[151]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
