{"id":"https://openalex.org/W3017313609","doi":"https://doi.org/10.3233/jcm-204175","title":"Improved method for compressive single-pixel imaging of a moving object","display_name":"Improved method for compressive single-pixel imaging of a moving object","publication_year":2020,"publication_date":"2020-04-14","ids":{"openalex":"https://openalex.org/W3017313609","doi":"https://doi.org/10.3233/jcm-204175","mag":"3017313609"},"language":"en","primary_location":{"id":"doi:10.3233/jcm-204175","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jcm-204175","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","raw_type":"journal-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/A5026348872","display_name":"Changjun Zha","orcid":"https://orcid.org/0000-0003-4534-9954"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]},{"id":"https://openalex.org/I39774598","display_name":"Hefei University","ror":"https://ror.org/01f5rdf64","country_code":"CN","type":"education","lineage":["https://openalex.org/I39774598"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Changjun Zha","raw_affiliation_strings":["Department of Electronics and Electrical Engineering, Hefei University, Hefei 230601, Anhui, China","Key Laboratory of Intelligent Computing and Signal Processing, Ministry of Education, Anhui University, Hefei 230039, Anhui, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Electrical Engineering, Hefei University, Hefei 230601, Anhui, China","institution_ids":["https://openalex.org/I39774598"]},{"raw_affiliation_string":"Key Laboratory of Intelligent Computing and Signal Processing, Ministry of Education, Anhui University, Hefei 230039, Anhui, China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5026348872"],"corresponding_institution_ids":["https://openalex.org/I143868143","https://openalex.org/I39774598"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0441909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":"4","first_page":"1175","last_page":"1181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T11996","display_name":"Random lasers and scattering media","score":0.9983000159263611,"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/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7318112850189209},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7072564363479614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6572400331497192},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6365737318992615},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6221838593482971},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.4908319115638733},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4715559482574463},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.43033555150032043},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4223233759403229},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4201244115829468},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34521394968032837}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7318112850189209},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7072564363479614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6572400331497192},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6365737318992615},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6221838593482971},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.4908319115638733},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4715559482574463},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.43033555150032043},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4223233759403229},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4201244115829468},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34521394968032837},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jcm-204175","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jcm-204175","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1744955113","https://openalex.org/W2022318697","https://openalex.org/W2029951924","https://openalex.org/W2060430274","https://openalex.org/W2099100030","https://openalex.org/W2100864539","https://openalex.org/W2106993026","https://openalex.org/W2122548617","https://openalex.org/W2127271355","https://openalex.org/W2164452299","https://openalex.org/W2248701860","https://openalex.org/W2291415704","https://openalex.org/W2342180957","https://openalex.org/W2467310651","https://openalex.org/W2519303799","https://openalex.org/W2546931742","https://openalex.org/W2653590625","https://openalex.org/W3043760823","https://openalex.org/W4250955649","https://openalex.org/W6719820393","https://openalex.org/W6781099322"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W4300044672","https://openalex.org/W2810730439","https://openalex.org/W1881631164","https://openalex.org/W2358292267","https://openalex.org/W2157715872","https://openalex.org/W2378166785","https://openalex.org/W1964277756","https://openalex.org/W2896778670"],"abstract_inverted_index":{"The":[0],"traditional":[1,43],"compressive":[2,14,35],"imaging":[3,36],"method":[4,33,127],"for":[5,34,115],"a":[6,68,92,136],"moving":[7,20,149],"object":[8,18,150],"has":[9],"the":[10,17,45,52,56,61,75,82,86,88,95,102,108,125,130,139,148],"problem":[11,133],"of":[12,94,141,147],"repeated":[13,131],"sampling":[15,132],"when":[16],"stops":[19],"or":[21],"remains":[22],"stationary.":[23],"To":[24],"solve":[25],"this":[26,28,38],"problem,":[27],"paper":[29],"presents":[30],"an":[31,142],"improved":[32],"in":[37,138],"situation.":[39],"In":[40],"contrast":[41],"to":[42,72],"methods,":[44],"image":[46,116],"is":[47,64,70,79,84,91,99,105,111],"preprocessed":[48],"before":[49],"reconstruction.":[50,117],"First,":[51],"Euclidean":[53],"distance":[54,83],"between":[55],"current":[57],"measurement":[58,77,89,103,109],"vector":[59,78,90,104],"and":[60,66,98,107,113,120],"previous":[62,96],"one":[63,97],"calculated,":[65],"then":[67],"threshold":[69],"used":[71,114],"determine":[73],"whether":[74],"new":[76],"valid.":[80],"If":[81],"below":[85],"threshold,":[87],"repetition":[93],"discarded;":[100],"otherwise,":[101],"valid":[106],"value":[110],"retained":[112],"Theoretical":[118],"analysis":[119],"simulation":[121],"results":[122],"show":[123],"that":[124],"proposed":[126],"can":[128],"eliminate":[129],"caused":[134],"by":[135],"pause":[137],"movement":[140],"object,":[143],"enabling":[144],"effective":[145],"reconstruction":[146],"image.":[151]},"counts_by_year":[],"updated_date":"2026-04-22T06:01:30.510260","created_date":"2025-10-10T00:00:00"}
