{"id":"https://openalex.org/W4372266977","doi":"https://doi.org/10.1109/icassp49357.2023.10095488","title":"Graph-Based Point Cloud Color Denoising with 3-Dimensional Patch-Based Similarity","display_name":"Graph-Based Point Cloud Color Denoising with 3-Dimensional Patch-Based Similarity","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372266977","doi":"https://doi.org/10.1109/icassp49357.2023.10095488"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10095488","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095488","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5060700521","display_name":"Ryosuke Watanabe","orcid":"https://orcid.org/0000-0002-0720-7763"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]},{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP","US"],"is_corresponding":false,"raw_author_name":"Ryosuke Watanabe","raw_affiliation_strings":["University of Southern California","KDDI Research, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California","institution_ids":["https://openalex.org/I2800817003","https://openalex.org/I1174212"]},{"raw_affiliation_string":"KDDI Research, Inc","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058963825","display_name":"Keisuke Nonaka","orcid":"https://orcid.org/0000-0002-9701-2862"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keisuke Nonaka","raw_affiliation_strings":["KDDI Research, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI Research, Inc","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034283584","display_name":"Eduardo Pav\u00e9z","orcid":"https://orcid.org/0000-0001-8985-2872"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eduardo Pavez","raw_affiliation_strings":["University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California","institution_ids":["https://openalex.org/I2800817003","https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032438911","display_name":"Tatsuya Kobayashi","orcid":"https://orcid.org/0000-0002-2869-6148"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tatsuya Kobayashi","raw_affiliation_strings":["KDDI Research, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI Research, Inc","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040001106","display_name":"Antonio Ortega","orcid":"https://orcid.org/0000-0001-5403-0940"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]},{"id":"https://openalex.org/I2800817003","display_name":"California Southern University","ror":"https://ror.org/058zz0t50","country_code":"US","type":"education","lineage":["https://openalex.org/I2800817003"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Antonio Ortega","raw_affiliation_strings":["University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California","institution_ids":["https://openalex.org/I2800817003","https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1228,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.79789965,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9977999925613403,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9977999925613403,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9955000281333923,"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/noise-reduction","display_name":"Noise reduction","score":0.7320717573165894},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6304694414138794},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5781572461128235},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5570201873779297},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5519208908081055},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.45639699697494507},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.43917930126190186},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4224897623062134},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3940417766571045},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3502974510192871},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.11831340193748474}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.7320717573165894},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6304694414138794},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5781572461128235},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5570201873779297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5519208908081055},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.45639699697494507},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.43917930126190186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4224897623062134},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3940417766571045},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3502974510192871},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.11831340193748474},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10095488","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095488","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7699999809265137}],"awards":[],"funders":[{"id":"https://openalex.org/F4320325628","display_name":"Ministry of Internal Affairs and Communications","ror":"https://ror.org/00vs1pz50"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1753163303","https://openalex.org/W1988392304","https://openalex.org/W1988874269","https://openalex.org/W2097063526","https://openalex.org/W2097073572","https://openalex.org/W2099244020","https://openalex.org/W2101491865","https://openalex.org/W2125527601","https://openalex.org/W2134236847","https://openalex.org/W2148089412","https://openalex.org/W2158361880","https://openalex.org/W2623075562","https://openalex.org/W2750342461","https://openalex.org/W2794319422","https://openalex.org/W2798965597","https://openalex.org/W2896671893","https://openalex.org/W2905544027","https://openalex.org/W2988447441","https://openalex.org/W3015965491","https://openalex.org/W3045749263","https://openalex.org/W3099141203","https://openalex.org/W3122628962","https://openalex.org/W3133749673","https://openalex.org/W3216006369","https://openalex.org/W4224920101","https://openalex.org/W4293518997","https://openalex.org/W4317600388","https://openalex.org/W6738675208"],"related_works":["https://openalex.org/W4389574804","https://openalex.org/W3016928466","https://openalex.org/W2936725271","https://openalex.org/W3150655618","https://openalex.org/W3108295644","https://openalex.org/W1578717197","https://openalex.org/W2626737336","https://openalex.org/W2005998065","https://openalex.org/W2980582925","https://openalex.org/W2065885792"],"abstract_inverted_index":{"Point":[0],"clouds":[1],"are":[2,33,68,124],"utilized":[3],"in":[4,74,98,114,136],"many":[5,60],"3-D":[6,14,24,95,106,166],"applications":[7],"such":[8,129],"as":[9,130],"cross-reality":[10],"(XR)":[11],"and":[12,26,134],"realistic":[13],"display.":[15],"They":[16],"consist":[17],"of":[18,21,43,86],"a":[19,51,71,90,141],"set":[20],"points":[22],"with":[23,104,116,176],"coordinates":[25],"associated":[27],"color":[28,31,57,66],"signals.":[29,58],"These":[30],"signals":[32],"often":[34],"perturbed":[35],"by":[36,39,83],"noise":[37,156],"induced":[38],"the":[40,75,84,100,109,146,154,171],"measurement":[41],"errors":[42],"scanning":[44],"devices.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49,139],"propose":[50,89,140],"point":[52,64,127,132],"cloud":[53,65],"denoising":[54,67,79,173],"method":[55,93,144],"for":[56,63,121],"Since":[59],"conventional":[61,117],"methods":[62,120],"based":[69,125],"on":[70,126,153],"low-pass":[72,142],"filter":[73],"graph":[76,91,118],"spectral":[77],"domain,":[78],"accuracy":[80,174],"is":[81,102,113,149],"affected":[82],"choice":[85],"graph.":[87],"We":[88],"construction":[92,119],"using":[94],"patch-based":[96,167],"similarity,":[97],"which":[99,123],"similarity":[101,168],"calculated":[103],"small":[105],"patches":[107],"around":[108],"connected":[110],"points.":[111],"This":[112],"contrast":[115],"denoising,":[122],"properties":[128],"pairwise":[131],"distances":[133],"differences":[135],"color.":[137],"Second,":[138],"filtering":[143],"where":[145],"frequency":[147],"response":[148],"chosen":[150],"automatically":[151],"depending":[152],"estimated":[155],"level.":[157],"Our":[158],"experimental":[159],"results":[160],"show":[161],"that":[162],"our":[163],"proposed":[164],"method,":[165],"(3DPBS),":[169],"achieves":[170],"best":[172],"compared":[175],"graph-based":[177],"state-of-the-art":[178],"methods.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}