{"id":"https://openalex.org/W2774741750","doi":"https://doi.org/10.1109/mmsp.2017.8122233","title":"Estimating graph topology from sparse graph signals with an application to image denoising","display_name":"Estimating graph topology from sparse graph signals with an application to image denoising","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2774741750","doi":"https://doi.org/10.1109/mmsp.2017.8122233","mag":"2774741750"},"language":"en","primary_location":{"id":"doi:10.1109/mmsp.2017.8122233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp.2017.8122233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5083304019","display_name":"Darshan Batavia","orcid":null},"institutions":[{"id":"https://openalex.org/I98389781","display_name":"Dhirubhai Ambani University","ror":"https://ror.org/02d5b7g69","country_code":"IN","type":"education","lineage":["https://openalex.org/I98389781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Darshan Batavia","raw_affiliation_strings":["DAIICT, Gandhinagar"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DAIICT, Gandhinagar","institution_ids":["https://openalex.org/I98389781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002171548","display_name":"Aditya Tatu","orcid":"https://orcid.org/0000-0003-1851-7983"},"institutions":[{"id":"https://openalex.org/I98389781","display_name":"Dhirubhai Ambani University","ror":"https://ror.org/02d5b7g69","country_code":"IN","type":"education","lineage":["https://openalex.org/I98389781"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Aditya Tatu","raw_affiliation_strings":["DAIICT, Gandhinagar"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DAIICT, Gandhinagar","institution_ids":["https://openalex.org/I98389781"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98389781"],"apc_list":null,"apc_paid":null,"fwci":0.1384,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46101743,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9965999722480774,"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/laplacian-matrix","display_name":"Laplacian matrix","score":0.5651557445526123},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5143035650253296},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4911749064922333},{"id":"https://openalex.org/keywords/graph-bandwidth","display_name":"Graph bandwidth","score":0.4827994108200073},{"id":"https://openalex.org/keywords/topological-graph-theory","display_name":"Topological graph theory","score":0.4780638515949249},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.46824800968170166},{"id":"https://openalex.org/keywords/graph-energy","display_name":"Graph energy","score":0.46124619245529175},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4474850594997406},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4393618404865265},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.34121498465538025},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34019336104393005},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3391018509864807},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.27210408449172974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2676735520362854},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07312813401222229}],"concepts":[{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.5651557445526123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5143035650253296},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4911749064922333},{"id":"https://openalex.org/C134727501","wikidata":"https://www.wikidata.org/wiki/Q5597073","display_name":"Graph bandwidth","level":5,"score":0.4827994108200073},{"id":"https://openalex.org/C157406716","wikidata":"https://www.wikidata.org/wiki/Q4115842","display_name":"Topological graph theory","level":5,"score":0.4780638515949249},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.46824800968170166},{"id":"https://openalex.org/C78913703","wikidata":"https://www.wikidata.org/wiki/Q5597087","display_name":"Graph energy","level":5,"score":0.46124619245529175},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4474850594997406},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4393618404865265},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.34121498465538025},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34019336104393005},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3391018509864807},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.27210408449172974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2676735520362854},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07312813401222229}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mmsp.2017.8122233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp.2017.8122233","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W747911303","https://openalex.org/W1565795754","https://openalex.org/W1684305122","https://openalex.org/W1976768677","https://openalex.org/W1991252559","https://openalex.org/W2011181254","https://openalex.org/W2044810215","https://openalex.org/W2101491865","https://openalex.org/W2109449402","https://openalex.org/W2140856955","https://openalex.org/W2158940042","https://openalex.org/W2469963130","https://openalex.org/W2486096428","https://openalex.org/W2963818281","https://openalex.org/W2964012239","https://openalex.org/W3123837026","https://openalex.org/W4214806317","https://openalex.org/W6719831127"],"related_works":["https://openalex.org/W2575552581","https://openalex.org/W2963150133","https://openalex.org/W3170778148","https://openalex.org/W2311733247","https://openalex.org/W4318995835","https://openalex.org/W4254484011","https://openalex.org/W3010598402","https://openalex.org/W2800334336","https://openalex.org/W2884933631","https://openalex.org/W2774741750"],"abstract_inverted_index":{"Graph":[0,42],"signal":[1,23,48],"processing":[2],"is":[3,49,123,155],"a":[4,30,45],"framework":[5,88],"that":[6,16,72,89,142,146],"allows":[7],"us":[8],"to":[9,95,108,125,157,159],"work":[10],"with":[11,20,147,167],"general":[12],"unstructured":[13],"discrete":[14],"data":[15],"cannot":[17],"be":[18,57],"handled":[19],"classical":[21],"Discrete":[22],"processing.":[24],"The":[25],"underlying":[26],"graph":[27,47,68,82,99,116,169],"topology":[28,43,69,149],"plays":[29],"crucial":[31],"role":[32],"in":[33,75,85,92],"determining":[34],"the":[35,64,76,81,98,152,168,174],"definition":[36],"of":[37,66],"Fourier":[38,103],"transform":[39],"on":[40,136],"graphs.":[41],"for":[44,112,129],"given":[46],"not":[50,56],"always":[51],"available":[52],"and":[53,101,139,173],"may":[54],"also":[55,106],"unique.":[58],"In":[59],"this":[60,110],"paper":[61],"we":[62],"address":[63],"problem":[65],"estimating":[67],"from":[70],"signals":[71,100],"are":[73],"sparse":[74],"frequency":[77],"domain.":[78],"We":[79,105,133,163],"estimate":[80],"Laplacian":[83],"matrix":[84],"an":[86,114],"optimization":[87],"minimizes":[90],"errors":[91],"relations":[93],"known":[94,124],"exist":[96],"between":[97],"their":[102],"transforms.":[104],"propose":[107],"use":[109],"algorithm":[111,151,154],"adapting":[113],"existing":[115],"based":[117,170],"non-local":[118,171],"image":[119,161],"denoising":[120,153],"algorithm,":[121,177],"which":[122],"perform":[126],"well":[127],"only":[128],"piece-wise":[130],"smooth":[131,140],"images.":[132],"provide":[134],"results":[135,166],"natural,":[137],"texture":[138],"images":[141],"support":[143],"our":[144,148,165],"claim":[145],"estimation":[150],"able":[156],"adapt":[158],"different":[160,179],"structures.":[162],"compare":[164],"method":[172],"state-of-art":[175],"BM3D":[176],"using":[178],"performance":[180],"measures.":[181]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}