{"id":"https://openalex.org/W4386230932","doi":"https://doi.org/10.1109/tmm.2023.3305828","title":"When Channel Correlation Meets Sparse Prior: Keeping Interpretability in Image Compressive Sensing","display_name":"When Channel Correlation Meets Sparse Prior: Keeping Interpretability in Image Compressive Sensing","publication_year":2023,"publication_date":"2023-08-28","ids":{"openalex":"https://openalex.org/W4386230932","doi":"https://doi.org/10.1109/tmm.2023.3305828"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2023.3305828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3305828","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","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/A5076171663","display_name":"Xiaoyu Kong","orcid":"https://orcid.org/0009-0004-1386-9394"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Kong","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0004-1386-9394","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031480448","display_name":"Yongyong Chen","orcid":"https://orcid.org/0000-0003-1970-1993"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongyong Chen","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-1970-1993","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100740564","display_name":"Zhenyu He","orcid":"https://orcid.org/0000-0002-2546-8721"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu He","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China","Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-2546-8721","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6525,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.81297451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"26","issue":null,"first_page":"2953","last_page":"2965"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9990000128746033,"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/T11778","display_name":"Electrical and Bioimpedance Tomography","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/interpretability","display_name":"Interpretability","score":0.821468710899353},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7974841594696045},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.69547438621521},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5190661549568176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5107424259185791},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4871763586997986},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4756193459033966},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.43451541662216187},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4270431697368622},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3884370028972626},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.17354312539100647}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.821468710899353},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7974841594696045},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.69547438621521},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5190661549568176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5107424259185791},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4871763586997986},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4756193459033966},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.43451541662216187},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4270431697368622},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3884370028972626},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.17354312539100647},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2023.3305828","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3305828","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1570251590","display_name":null,"funder_award_id":"62106063","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3911502178","display_name":null,"funder_award_id":"2022A1515010819","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G8156069797","display_name":null,"funder_award_id":"62172126","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W1791560514","https://openalex.org/W1979479847","https://openalex.org/W2018990310","https://openalex.org/W2034118716","https://openalex.org/W2045737896","https://openalex.org/W2047920195","https://openalex.org/W2049819383","https://openalex.org/W2073437729","https://openalex.org/W2082029531","https://openalex.org/W2085899807","https://openalex.org/W2086782272","https://openalex.org/W2093621384","https://openalex.org/W2100556411","https://openalex.org/W2103375347","https://openalex.org/W2122548617","https://openalex.org/W2124587329","https://openalex.org/W2127271355","https://openalex.org/W2141168890","https://openalex.org/W2154304330","https://openalex.org/W2162409952","https://openalex.org/W2191349405","https://openalex.org/W2273561594","https://openalex.org/W2508457857","https://openalex.org/W2526377930","https://openalex.org/W2543013670","https://openalex.org/W2556068545","https://openalex.org/W2563032747","https://openalex.org/W2569021273","https://openalex.org/W2613155248","https://openalex.org/W2752782242","https://openalex.org/W2798559986","https://openalex.org/W2902719825","https://openalex.org/W2923415235","https://openalex.org/W2949128855","https://openalex.org/W2955058313","https://openalex.org/W2962974137","https://openalex.org/W2963081547","https://openalex.org/W2963676935","https://openalex.org/W2965405987","https://openalex.org/W2974585710","https://openalex.org/W3009991223","https://openalex.org/W3018622322","https://openalex.org/W3033835243","https://openalex.org/W3048134800","https://openalex.org/W3086415202","https://openalex.org/W3092407891","https://openalex.org/W3102025760","https://openalex.org/W3115447952","https://openalex.org/W3134510327","https://openalex.org/W3135630532","https://openalex.org/W3135885438","https://openalex.org/W3167568784","https://openalex.org/W3169761664","https://openalex.org/W3170881570","https://openalex.org/W3188921881","https://openalex.org/W3190499751","https://openalex.org/W3207346178","https://openalex.org/W3207407006","https://openalex.org/W4200596895","https://openalex.org/W4234992901","https://openalex.org/W4250482878","https://openalex.org/W4250955649","https://openalex.org/W4289752563","https://openalex.org/W4292363360","https://openalex.org/W4292387271","https://openalex.org/W4293518946","https://openalex.org/W4302067267","https://openalex.org/W4364322808","https://openalex.org/W4394642372","https://openalex.org/W6739495466","https://openalex.org/W6739675538","https://openalex.org/W6757612955"],"related_works":["https://openalex.org/W2091883426","https://openalex.org/W3173235360","https://openalex.org/W2737338842","https://openalex.org/W2174948646","https://openalex.org/W3005946484","https://openalex.org/W2024017047","https://openalex.org/W4318256793","https://openalex.org/W2051410394","https://openalex.org/W2594370889","https://openalex.org/W2390720471"],"abstract_inverted_index":{"Image":[0],"compressive":[1],"sensing":[2],"(CS),":[3],"recovering":[4],"an":[5,19],"unknown":[6],"image":[7,75,165,207],"by":[8],"resorting":[9],"to":[10,39,137,172],"a":[11,29,62,113,122,181],"small":[12],"number":[13],"of":[14,116,163],"its":[15],"measurements,":[16],"has":[17],"become":[18],"increasingly":[20],"popular":[21],"topic":[22],"in":[23,142,160,193],"multimedia":[24],"technology":[25],"and":[26,52,65,80,167,195,213],"applications.":[27],"For":[28],"better":[30,114],"reconstruction,":[31],"diverse":[32],"priors,":[33],"from":[34,133],"the":[35,40,48,56,83,102,106,117,131,139,143,164,173,201,205],"original":[36],"sparse":[37,87],"prior":[38,58,88,96,99],"new":[41],"deep":[42,57,95,214],"prior,":[43],"have":[44],"been":[45],"exploited.":[46],"Despite":[47],"powerful":[49],"learning":[50],"capability":[51],"satisfactory":[53],"reconstruction":[54],"performance,":[55],"is":[59,108],"known":[60],"as":[61],"black":[63],"box":[64],"loses":[66],"clear":[67],"interpretability.":[68],"In":[69],"this":[70],"article,":[71],"we":[72,120],"first":[73],"revisit":[74],"CS":[76,208],"with":[77,85,94,210],"different":[78],"priors":[79],"observe":[81],"that":[82],"method":[84,203],"hand-crafted":[86],"could":[89],"still":[90],"outperform":[91],"state-of-art":[92],"methods":[93,209],"or":[97],"no":[98],"when":[100],"under":[101],"same":[103],"settings,":[104],"while":[105],"interpretability":[107],"well":[109],"preserved.":[110],"Then,":[111],"towards":[112],"performance":[115],"sparse-prior-based":[118],"method,":[119],"propose":[121],"Channel":[123],"Adaptive":[124],"Thresholding":[125],"Network,":[126],"namely":[127],"CAT-Net.":[128],"CAT-Net":[129],"draws":[130],"support":[132],"channel":[134,153,162],"correlation":[135],"calculation":[136],"extend":[138],"single":[140,182],"thresholding":[141,146,155,158],"iterative":[144],"soft":[145,157],"algorithm":[147],"(ISTA)":[148],"into":[149],"channel-wise":[150],"thresholding.":[151,184],"The":[152,185],"adaptive":[154],"conducts":[156],"operation":[159,188],"each":[161],"features":[166],"can":[168,176,189],"be":[169],"adjusted":[170],"adaptively":[171],"inputs,":[174],"which":[175],"reconstruct":[177],"more":[178],"precisely":[179],"than":[180],"static":[183],"careful":[186],"CAT":[187],"preserve":[190],"patterns":[191],"both":[192,211],"detail":[194],"holistically":[196],"well.":[197],"Experimental":[198],"results":[199],"demonstrate":[200],"proposed":[202],"outperforms":[204],"state-of-the-art":[206],"traditional":[212],"priors.":[215]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}