{"id":"https://openalex.org/W2158717601","doi":"https://doi.org/10.1145/1143844.1143922","title":"Learning high-order MRF priors of color images","display_name":"Learning high-order MRF priors of color images","publication_year":2006,"publication_date":"2006-01-01","ids":{"openalex":"https://openalex.org/W2158717601","doi":"https://doi.org/10.1145/1143844.1143922","mag":"2158717601"},"language":"en","primary_location":{"id":"doi:10.1145/1143844.1143922","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1143844.1143922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd international conference on Machine learning  - ICML '06","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/A5021827617","display_name":"Julian McAuley","orcid":"https://orcid.org/0000-0003-0955-7588"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Julian J. McAuley","raw_affiliation_strings":["National ICT Australia, Canberra, Australia and University of New South Wales, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"National ICT Australia, Canberra, Australia and University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I42894916","https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030482411","display_name":"Tib\u00e9rio S. Caetano","orcid":null},"institutions":[{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tib\u00e9rio S. Caetano","raw_affiliation_strings":["National ICT Australia, Canberra, Australia and RSISE, Australian National University, Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"National ICT Australia, Canberra, Australia and RSISE, Australian National University, Canberra, Australia","institution_ids":["https://openalex.org/I118347636","https://openalex.org/I42894916"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090351022","display_name":"Alex Smola","orcid":null},"institutions":[{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Alex J. Smola","raw_affiliation_strings":["National ICT Australia, Canberra, Australia and RSISE, Australian National University, Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"National ICT Australia, Canberra, Australia and RSISE, Australian National University, Canberra, Australia","institution_ids":["https://openalex.org/I118347636","https://openalex.org/I42894916"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012844162","display_name":"Matthias Franz","orcid":"https://orcid.org/0000-0003-3789-8849"},"institutions":[{"id":"https://openalex.org/I4210112925","display_name":"Max Planck Institute for Biological Cybernetics","ror":"https://ror.org/026nmvv73","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210112925"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Matthias O. Franz","raw_affiliation_strings":["Max Planck Institute for Biological Cybernetics, Tuebingen, Germany"],"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Biological Cybernetics, Tuebingen, Germany","institution_ids":["https://openalex.org/I4210112925"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5021827617"],"corresponding_institution_ids":["https://openalex.org/I31746571","https://openalex.org/I42894916"],"apc_list":null,"apc_paid":null,"fwci":4.0489,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.9464476,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"617","last_page":"624"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994000196456909,"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":0.9994000196456909,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9965000152587891,"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/prior-probability","display_name":"Prior probability","score":0.7010631561279297},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6969917416572571},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.611226499080658},{"id":"https://openalex.org/keywords/monochromatic-color","display_name":"Monochromatic color","score":0.5973897576332092},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5842841267585754},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.5422753095626831},{"id":"https://openalex.org/keywords/clique","display_name":"Clique","score":0.48781612515449524},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4500267803668976},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4219704866409302},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4047098755836487},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38646310567855835},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29044875502586365},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.203243225812912}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7010631561279297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6969917416572571},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.611226499080658},{"id":"https://openalex.org/C40833965","wikidata":"https://www.wikidata.org/wiki/Q6901438","display_name":"Monochromatic color","level":2,"score":0.5973897576332092},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5842841267585754},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.5422753095626831},{"id":"https://openalex.org/C2777035058","wikidata":"https://www.wikidata.org/wiki/Q1662634","display_name":"Clique","level":2,"score":0.48781612515449524},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4500267803668976},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4219704866409302},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4047098755836487},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38646310567855835},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29044875502586365},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.203243225812912},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1143844.1143922","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1143844.1143922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd international conference on Machine learning  - ICML '06","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8600000143051147,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2014403078","https://openalex.org/W2079182758","https://openalex.org/W2105464873","https://openalex.org/W2121927366","https://openalex.org/W2130159466","https://openalex.org/W2131686571","https://openalex.org/W2137186219","https://openalex.org/W2138448681","https://openalex.org/W2146914716","https://openalex.org/W2149760002","https://openalex.org/W2150920547","https://openalex.org/W2158646162"],"related_works":["https://openalex.org/W2337415362","https://openalex.org/W4312857205","https://openalex.org/W121273120","https://openalex.org/W2740820121","https://openalex.org/W317572212","https://openalex.org/W2002009170","https://openalex.org/W2034462085","https://openalex.org/W2546871836","https://openalex.org/W2141888456","https://openalex.org/W2136485282"],"abstract_inverted_index":{"In":[0,34],"this":[1],"paper,":[2],"we":[3],"use":[4],"large":[5,47],"neighborhood":[6],"Markov":[7],"random":[8],"fields":[9],"to":[10,31,45,58,66,77],"learn":[11],"rich":[12],"prior":[13],"models":[14],"of":[15,24,37,42,61,89],"color":[16,32,90],"images.":[17,33,91],"Our":[18],"approach":[19,69],"extends":[20],"the":[21,35,40,54,67,80],"monochromatic":[22,104],"Fields":[23,36],"Experts":[25,38],"model":[26],"(Roth":[27],"&":[28],"Black,":[29],"2005a)":[30],"model,":[39],"curse":[41],"dimensionality":[43],"due":[44],"very":[46],"clique":[48,82],"sizes":[49],"is":[50],"circumvented":[51],"by":[52,70],"parameterizing":[53],"potential":[55],"functions":[56],"according":[57],"a":[59],"product":[60],"experts.":[62],"We":[63],"introduce":[64],"simplifications":[65],"original":[68],"Roth":[71],"and":[72],"Black":[73],"which":[74,99],"allow":[75],"us":[76],"cope":[78],"with":[79],"increased":[81],"size":[83],"(typically":[84],"3x3x3":[85],"or":[86],"5x5x3":[87],"pixels)":[88],"Experimental":[92],"results":[93],"are":[94],"presented":[95],"for":[96],"image":[97,105],"denoising":[98],"evidence":[100],"improvements":[101],"over":[102],"state-of-the-art":[103],"priors.":[106]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}