{"id":"https://openalex.org/W2963764784","doi":"https://doi.org/10.1109/icip.2016.7532817","title":"Generalized alternating projection based total variation minimization for compressive sensing","display_name":"Generalized alternating projection based total variation minimization for compressive sensing","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2963764784","doi":"https://doi.org/10.1109/icip.2016.7532817","mag":"2963764784"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7532817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","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/A5015431603","display_name":"Xin Yuan","orcid":"https://orcid.org/0000-0002-8311-7524"},"institutions":[{"id":"https://openalex.org/I4210162091","display_name":"Bellbrook Labs (United States)","ror":"https://ror.org/05eewjw07","country_code":"US","type":"company","lineage":["https://openalex.org/I4210162091"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xin Yuan","raw_affiliation_strings":["Bell Labs, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bell Labs, NJ, USA","institution_ids":["https://openalex.org/I4210162091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5015431603"],"corresponding_institution_ids":["https://openalex.org/I4210162091"],"apc_list":null,"apc_paid":null,"fwci":13.2031,"has_fulltext":false,"cited_by_count":355,"citation_normalized_percentile":{"value":0.99290698,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2539","last_page":"2543"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8497991561889648},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.8253626227378845},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.7492212653160095},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5915990471839905},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5688275098800659},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5023934841156006},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43250176310539246},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4142169952392578},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3338509798049927},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32493099570274353},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.2850020229816437}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8497991561889648},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.8253626227378845},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.7492212653160095},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5915990471839905},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5688275098800659},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5023934841156006},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43250176310539246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4142169952392578},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3338509798049927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32493099570274353},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2850020229816437}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2016.7532817","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532817","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W980527010","https://openalex.org/W1789591995","https://openalex.org/W1968367053","https://openalex.org/W1978333359","https://openalex.org/W1985894000","https://openalex.org/W1986213393","https://openalex.org/W1986701690","https://openalex.org/W1992653101","https://openalex.org/W1998252084","https://openalex.org/W2005361584","https://openalex.org/W2018990310","https://openalex.org/W2028339660","https://openalex.org/W2028349405","https://openalex.org/W2031227834","https://openalex.org/W2043447070","https://openalex.org/W2048364349","https://openalex.org/W2087323249","https://openalex.org/W2097273723","https://openalex.org/W2130120519","https://openalex.org/W2142224912","https://openalex.org/W2163973643","https://openalex.org/W2164278908","https://openalex.org/W2212988997","https://openalex.org/W2217417683","https://openalex.org/W2222485310","https://openalex.org/W2249299093","https://openalex.org/W2254948053","https://openalex.org/W2266216861","https://openalex.org/W2315002515","https://openalex.org/W2320606762","https://openalex.org/W2335050829","https://openalex.org/W2963999426","https://openalex.org/W3103783116","https://openalex.org/W3104984874","https://openalex.org/W4292363360","https://openalex.org/W6649953083","https://openalex.org/W6688742367","https://openalex.org/W6691294777","https://openalex.org/W6691386815","https://openalex.org/W6693482253"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W2027399350","https://openalex.org/W2060875994","https://openalex.org/W2044184146","https://openalex.org/W2019190440","https://openalex.org/W3034864990","https://openalex.org/W2208932071"],"abstract_inverted_index":{"We":[0,42],"consider":[1],"the":[2,16,25,45,64],"total":[3],"variation":[4],"(TV)":[5],"minimization":[6,55],"problem":[7],"used":[8],"for":[9,56],"compressive":[10,32,61],"sensing":[11,62],"and":[12,40,58,66,73],"solve":[13],"it":[14],"using":[15],"generalized":[17],"alternating":[18],"projection":[19],"(GAP)":[20],"algorithm.":[21],"Extensive":[22],"results":[23],"demonstrate":[24],"high":[26],"performance":[27],"of":[28,49],"proposed":[29],"algorithm":[30],"on":[31],"sensing,":[33],"including":[34],"two":[35],"dimensional":[36],"images,":[37],"hyperspectral":[38,59],"images":[39],"videos.":[41],"further":[43],"derive":[44],"Alternating":[46],"Direction":[47],"Method":[48],"Multipliers":[50],"(ADMM)":[51],"framework":[52],"with":[53],"TV":[54],"video":[57],"image":[60],"under":[63],"CACTI":[65],"CASSI":[67],"framework,":[68],"respectively.":[69],"Connections":[70],"between":[71],"GAP":[72],"ADMM":[74],"are":[75],"also":[76],"provided.":[77]},"counts_by_year":[{"year":2026,"cited_by_count":21},{"year":2025,"cited_by_count":62},{"year":2024,"cited_by_count":74},{"year":2023,"cited_by_count":62},{"year":2022,"cited_by_count":38},{"year":2021,"cited_by_count":43},{"year":2020,"cited_by_count":30},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":3}],"updated_date":"2026-08-22T07:34:49.880490","created_date":"2025-10-10T00:00:00"}