{"id":"https://openalex.org/W2964222715","doi":"https://doi.org/10.1109/icme.2018.8486521","title":"Full Image Recover for Block-Based Compressive Sensing","display_name":"Full Image Recover for Block-Based Compressive Sensing","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2964222715","doi":"https://doi.org/10.1109/icme.2018.8486521","mag":"2964222715"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2018.8486521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2018.8486521","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Multimedia and Expo (ICME)","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/A5100458706","display_name":"Xuemei Xie","orcid":"https://orcid.org/0000-0001-7857-0845"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuemei Xie","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi'an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102845757","display_name":"Chenye Wang","orcid":"https://orcid.org/0000-0002-2412-0870"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenye Wang","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi'an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102816808","display_name":"Jiang Du","orcid":"https://orcid.org/0000-0002-3163-8846"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang Du","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi'an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101549504","display_name":"Guangming Shi","orcid":"https://orcid.org/0000-0003-2179-3292"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangming Shi","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi'an, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100458706"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":3.4455,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.9347733,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9988999962806702,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9987999796867371,"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/block","display_name":"Block (permutation group theory)","score":0.8567605018615723},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.802595853805542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.691385805606842},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6677793264389038},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6217127442359924},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5428798198699951},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5389261245727539},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20415344834327698}],"concepts":[{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.8567605018615723},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.802595853805542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.691385805606842},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6677793264389038},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6217127442359924},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5428798198699951},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5389261245727539},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20415344834327698},{"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/icme.2018.8486521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2018.8486521","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.75,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1977794869","https://openalex.org/W2056370875","https://openalex.org/W2065513175","https://openalex.org/W2109449402","https://openalex.org/W2115706991","https://openalex.org/W2129131372","https://openalex.org/W2194775991","https://openalex.org/W2219727625","https://openalex.org/W2273561594","https://openalex.org/W2289917018","https://openalex.org/W2402144811","https://openalex.org/W2578009003","https://openalex.org/W2590877996","https://openalex.org/W2741137940","https://openalex.org/W2762145983","https://openalex.org/W2771402530","https://openalex.org/W2953384591","https://openalex.org/W2962895431","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2964082260","https://openalex.org/W2964322393","https://openalex.org/W3102722370","https://openalex.org/W6713134421"],"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/W2012905040","https://openalex.org/W2503689422","https://openalex.org/W2896778670"],"abstract_inverted_index":{"Compressive":[0],"sensing":[1],"(CS)":[2],"theory":[3],"is":[4,43,79,130,137],"able":[5],"to":[6,45,69,84,102],"acquire":[7,85],"measurements":[8,95],"of":[9,34],"a":[10,63,148],"scene":[11,18],"at":[12,141],"sub-Nyquist":[13],"rate":[14],"and":[15],"recover":[16,46],"the":[17,32,74,77,86,90,94,104,116,120,125,144],"image":[19,98],"from":[20,48,96,108],"these":[21],"under-sampled":[22],"measurements.":[23,87],"Recent":[24],"years,":[25],"CS":[26,68],"has":[27,153],"been":[28],"improved":[29],"greatly":[30],"for":[31,67],"application":[33],"deep":[35],"learning":[36],"technology.":[37],"In":[38,58,73],"conventional":[39],"methods,":[40],"block-based":[41],"mechanism":[42],"used":[44,100],"images":[47,112],"measurements,":[49],"which":[50],"usually":[51],"causes":[52],"block":[53,81,83,113,139],"effect":[54,129,140],"in":[55,89,124,143,156],"reconstructed":[56,145],"images.":[57,146],"this":[59,71],"paper,":[60],"we":[61],"propose":[62],"novel":[64],"CNN-based":[65],"network":[66],"solve":[70],"problem.":[72],"measurement":[75,126],"part,":[76,92],"input":[78],"measured":[80],"by":[82,114],"While":[88],"recovery":[91],"all":[93,142],"one":[97],"are":[99],"simultaneously":[101],"reconstruct":[103],"full":[105],"image.":[106],"Different":[107],"previous":[109],"methods":[110],"recovering":[111],"block,":[115],"proposed":[117],"framework":[118],"rebuilds":[119],"structure":[121],"information":[122],"destroyed":[123],"part.":[127],"Block":[128],"removed":[131],"accordingly.":[132],"Experiments":[133],"show":[134],"that":[135],"there":[136],"no":[138],"On":[147],"standard":[149],"dataset":[150],"our":[151],"method":[152],"significant":[154],"improvements":[155],"reconstruction":[157],"results":[158],"compared":[159],"with":[160],"existing":[161],"state-of-the-art":[162],"methods.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}