{"id":"https://openalex.org/W1969430823","doi":"https://doi.org/10.1109/icme.2014.6890254","title":"Image compressive-sensing recovery using structured laplacian sparsity in DCT domain and multi-hypothesis prediction","display_name":"Image compressive-sensing recovery using structured laplacian sparsity in DCT domain and multi-hypothesis prediction","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W1969430823","doi":"https://doi.org/10.1109/icme.2014.6890254","mag":"1969430823"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2014.6890254","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2014.6890254","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Multimedia and Expo (ICME)","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/A5101993842","display_name":"Chen Zhao","orcid":"https://orcid.org/0000-0003-4993-5416"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Zhao","raw_affiliation_strings":["Institute of Digital Media, Peking University, Beijing, China","[Institute of Digital Media, Peking University, Beijing, China.]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"[Institute of Digital Media, Peking University, Beijing, China.]","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039832462","display_name":"Siwei Ma","orcid":"https://orcid.org/0000-0002-2731-5403"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siwei Ma","raw_affiliation_strings":["Institute of Digital Media, Peking University, Beijing, China","[Institute of Digital Media, Peking University, Beijing, China.]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"[Institute of Digital Media, Peking University, Beijing, China.]","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018478553","display_name":"Wen Gao","orcid":"https://orcid.org/0000-0002-8070-802X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Gao","raw_affiliation_strings":["Institute of Digital Media, Peking University, Beijing, China","[Institute of Digital Media, Peking University, Beijing, China.]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Digital Media, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"[Institute of Digital Media, Peking University, Beijing, China.]","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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":0.9998000264167786,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9994999766349792,"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/compressed-sensing","display_name":"Compressed sensing","score":0.712888240814209},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.6861667633056641},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6309210062026978},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6095468401908875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5981810688972473},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5762376189231873},{"id":"https://openalex.org/keywords/laplace-operator","display_name":"Laplace operator","score":0.5292056798934937},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5254932045936584},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5115891098976135},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4687725901603699},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.42433324456214905},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.422066330909729},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38021472096443176},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3391927182674408},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3293112516403198}],"concepts":[{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.712888240814209},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.6861667633056641},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6309210062026978},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6095468401908875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5981810688972473},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5762376189231873},{"id":"https://openalex.org/C165700671","wikidata":"https://www.wikidata.org/wiki/Q203484","display_name":"Laplace operator","level":2,"score":0.5292056798934937},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5254932045936584},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5115891098976135},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4687725901603699},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.42433324456214905},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.422066330909729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38021472096443176},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3391927182674408},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3293112516403198},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2014.6890254","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2014.6890254","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Multimedia and Expo (ICME)","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":28,"referenced_works":["https://openalex.org/W340244495","https://openalex.org/W1895520453","https://openalex.org/W1979479847","https://openalex.org/W1984077106","https://openalex.org/W2002969407","https://openalex.org/W2049502219","https://openalex.org/W2049819383","https://openalex.org/W2085899807","https://openalex.org/W2086670019","https://openalex.org/W2097073572","https://openalex.org/W2117865218","https://openalex.org/W2127295759","https://openalex.org/W2142058898","https://openalex.org/W2145096794","https://openalex.org/W2159092888","https://openalex.org/W2164566711","https://openalex.org/W2196956961","https://openalex.org/W2296616510","https://openalex.org/W2543013670","https://openalex.org/W3104720471","https://openalex.org/W4250955649","https://openalex.org/W4300263211","https://openalex.org/W6639630648","https://openalex.org/W6662814034","https://openalex.org/W6671975367","https://openalex.org/W6672498978","https://openalex.org/W6683373869","https://openalex.org/W6729122150"],"related_works":["https://openalex.org/W1916685473","https://openalex.org/W2055682261","https://openalex.org/W1993363272","https://openalex.org/W2896778670","https://openalex.org/W2107386309","https://openalex.org/W2545869789","https://openalex.org/W2141090006","https://openalex.org/W1964555484","https://openalex.org/W3048932468","https://openalex.org/W2148504016"],"abstract_inverted_index":{"In":[0],"compressive":[1],"sensing":[2],"(CS),":[3],"the":[4,26,52,63,74,97,100,109,114,134,138],"seeking":[5],"of":[6,11,20,56,65,77,99],"a":[7,16,30],"fair":[8],"domain":[9,33],"is":[10,70],"essentially":[12],"significance":[13],"to":[14,50,62,96],"achieve":[15],"high":[17],"enough":[18,40],"degree":[19],"signal":[21],"sparsity.":[22],"Most":[23],"methods":[24,141],"in":[25,142],"literature,":[27],"however,":[28],"use":[29],"fixed":[31],"transform":[32],"or":[34],"prior":[35],"information":[36],"that":[37,133],"cannot":[38],"exhibit":[39],"sparsity":[41,55,69],"for":[42,89,107],"various":[43],"images.":[44,67],"Superiorly,":[45],"we":[46,117],"propose":[47],"an":[48,119],"algorithm":[49,136],"explore":[51],"structured":[53,82,101],"Laplacian":[54],"DCT":[57],"coefficients,":[58],"which":[59],"can":[60],"adapt":[61],"non-stationarity":[64],"natural":[66,78],"Better":[68],"achieved":[71],"by":[72],"utilizing":[73],"nonlocal":[75],"similarity":[76],"images":[79],"and":[80,103,145],"constructing":[81],"image":[83],"patch":[84],"groups.":[85],"Meanwhile,":[86],"multiple":[87],"hypotheses":[88],"each":[90],"pixel":[91],"could":[92],"be":[93],"obtained":[94],"owing":[95],"overlapping":[98],"groups":[102],"similar":[104],"patches.":[105],"Additionally,":[106],"solving":[108],"optimization":[110],"problem":[111],"formulated":[112],"from":[113],"techniques":[115],"above,":[116],"design":[118],"efficient":[120],"iterative":[121],"method":[122],"based":[123],"on":[124],"split":[125],"Bregman":[126],"iteration":[127],"(SBI)":[128],"algorithm.":[129],"Experimental":[130],"results":[131],"demonstrate":[132],"proposed":[135],"outperforms":[137],"other":[139],"state-of-the-art":[140],"both":[143],"objective":[144],"subjective":[146],"recovery":[147],"quality.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
