{"id":"https://openalex.org/W3015285636","doi":"https://doi.org/10.1109/icassp40776.2020.9053414","title":"Preconditioned Ghost Imaging Via Sparsity Constraint","display_name":"Preconditioned Ghost Imaging Via Sparsity Constraint","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015285636","doi":"https://doi.org/10.1109/icassp40776.2020.9053414","mag":"3015285636"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053414","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053414","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 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/A5023197519","display_name":"Zhishen Tong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135349","display_name":"Shanghai Institute of Optics and Fine Mechanics","ror":"https://ror.org/03g897070","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210135349"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhishen Tong","raw_affiliation_strings":["Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, China","institution_ids":["https://openalex.org/I4210135349"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100370396","display_name":"Jian Wang","orcid":"https://orcid.org/0000-0002-0579-3041"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["School of Data Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084317657","display_name":"Shensheng Han","orcid":"https://orcid.org/0000-0003-1689-5876"},"institutions":[{"id":"https://openalex.org/I4210135349","display_name":"Shanghai Institute of Optics and Fine Mechanics","ror":"https://ror.org/03g897070","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210135349"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shensheng Han","raw_affiliation_strings":["Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, China","institution_ids":["https://openalex.org/I4210135349"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5023197519"],"corresponding_institution_ids":["https://openalex.org/I4210135349"],"apc_list":null,"apc_paid":null,"fwci":0.2149,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.36519608,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"182","issue":null,"first_page":"1484","last_page":"1488"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11996","display_name":"Random lasers and scattering media","score":1.0,"subfield":{"id":"https://openalex.org/subfields/3102","display_name":"Acoustics and Ultrasonics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11996","display_name":"Random lasers and scattering media","score":1.0,"subfield":{"id":"https://openalex.org/subfields/3102","display_name":"Acoustics and Ultrasonics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9980000257492065,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9905999898910522,"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/sampling","display_name":"Sampling (signal processing)","score":0.590247631072998},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.554409921169281},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5336127281188965},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.4841650128364563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47500622272491455},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.42464709281921387},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4129665791988373},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34809136390686035},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.16499415040016174},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13562524318695068}],"concepts":[{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.590247631072998},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.554409921169281},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5336127281188965},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.4841650128364563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47500622272491455},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.42464709281921387},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4129665791988373},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34809136390686035},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.16499415040016174},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13562524318695068},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053414","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053414","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":32,"referenced_works":["https://openalex.org/W1897398438","https://openalex.org/W1979472147","https://openalex.org/W1981220107","https://openalex.org/W1981884787","https://openalex.org/W1998688147","https://openalex.org/W2006773459","https://openalex.org/W2031191822","https://openalex.org/W2058428247","https://openalex.org/W2065660946","https://openalex.org/W2076541487","https://openalex.org/W2078204800","https://openalex.org/W2087587668","https://openalex.org/W2090475034","https://openalex.org/W2102129292","https://openalex.org/W2109449402","https://openalex.org/W2127271355","https://openalex.org/W2128659236","https://openalex.org/W2129131372","https://openalex.org/W2134033146","https://openalex.org/W2142949395","https://openalex.org/W2160979406","https://openalex.org/W2171618086","https://openalex.org/W2211638162","https://openalex.org/W2296616510","https://openalex.org/W2734811486","https://openalex.org/W2963898043","https://openalex.org/W2980253183","https://openalex.org/W3098515897","https://openalex.org/W3101241281","https://openalex.org/W4250955649","https://openalex.org/W6645741999","https://openalex.org/W6768829568"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W2358292267","https://openalex.org/W2378166785","https://openalex.org/W1964277756","https://openalex.org/W2465351041","https://openalex.org/W1976264255"],"abstract_inverted_index":{"Ghost":[0],"imaging":[1,27,134],"via":[2],"sparsity":[3],"constraint":[4],"(GISC)":[5],"can":[6],"recover":[7],"objects":[8],"from":[9,102],"the":[10,22,33,54,69,75,82,90,108,138],"intensity":[11],"fluctuation":[12],"of":[13,35,64,77,107],"light":[14],"fields":[15],"at":[16],"a":[17],"sampling":[18,36,78],"rate":[19],"far":[20],"below":[21],"Nyquist":[23],"rate.":[24],"However,":[25],"its":[26],"quality":[28,135],"may":[29],"degrade":[30],"severely":[31],"when":[32],"coherence":[34,76],"matrices":[37,79],"is":[38],"large.":[39],"To":[40],"deal":[41],"with":[42,110],"this":[43],"issue,":[44],"we":[45],"propose":[46],"an":[47],"efficient":[48],"recovery":[49],"algorithm":[50,62,88],"for":[51],"GISC":[52],"called":[53],"preconditioned":[55],"multiple":[56,83],"orthogonal":[57,84],"least":[58,85],"squares":[59,86],"(PmOLS).":[60],"Our":[61],"consists":[63],"two":[65],"major":[66],"parts:":[67],"i)":[68],"pseudo-inverse":[70],"preconditioning":[71],"(PIP)":[72],"method":[73],"refining":[74],"and":[80,127],"ii)":[81],"(mOLS)":[87],"recovering":[89],"objects.":[91],"Theoretical":[92],"analysis":[93],"shows":[94],"that":[95,130],"PmOLS":[96,131],"recovers":[97],"any":[98],"n-dimensional":[99],"K-sparse":[100],"signal":[101,109],"m":[103],"random":[104],"linear":[105],"samples":[106],"probability":[111],"exceeding":[112],"1-3n":[113],"<sup":[114,118,122],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[115,119,123],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[116,124],"e":[117],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">-cm</sup>":[120],"/K":[121],".":[125],"Simulations":[126],"experiments":[128],"demonstrate":[129],"has":[132],"competitive":[133],"compared":[136],"to":[137],"state-of-the-art":[139],"approaches.":[140]},"counts_by_year":[{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}