{"id":"https://openalex.org/W4416799700","doi":"https://doi.org/10.1109/apsipaasc65261.2025.11249070","title":"Distributed Compressed Video Sensing with Enhanced Boundary Handling Based on Extended Convolutional Sparse Representation","display_name":"Distributed Compressed Video Sensing with Enhanced Boundary Handling Based on Extended Convolutional Sparse Representation","publication_year":2025,"publication_date":"2025-10-22","ids":{"openalex":"https://openalex.org/W4416799700","doi":"https://doi.org/10.1109/apsipaasc65261.2025.11249070"},"language":null,"primary_location":{"id":"doi:10.1109/apsipaasc65261.2025.11249070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc65261.2025.11249070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5116226956","display_name":"Ibuki Muta","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099780","display_name":"National Institute of Technology, Kurume College","ror":"https://ror.org/00xefvv79","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210099780","https://openalex.org/I4210120810"]},{"id":"https://openalex.org/I4210132370","display_name":"National Institute of Technology, Kagoshima College","ror":"https://ror.org/02xm6sp43","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210120810","https://openalex.org/I4210132370"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ibuki Muta","raw_affiliation_strings":["National Institute of Technology (KOSEN), Kurume College,Fukuoka,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology (KOSEN), Kurume College,Fukuoka,Japan","institution_ids":["https://openalex.org/I4210099780","https://openalex.org/I4210132370"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046127561","display_name":"Yoshimitsu Kuroki","orcid":"https://orcid.org/0000-0003-4464-4329"},"institutions":[{"id":"https://openalex.org/I4210099780","display_name":"National Institute of Technology, Kurume College","ror":"https://ror.org/00xefvv79","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210099780","https://openalex.org/I4210120810"]},{"id":"https://openalex.org/I4210132370","display_name":"National Institute of Technology, Kagoshima College","ror":"https://ror.org/02xm6sp43","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210120810","https://openalex.org/I4210132370"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshimitsu Kuroki","raw_affiliation_strings":["National Institute of Technology (KOSEN), Kurume College,Fukuoka,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology (KOSEN), Kurume College,Fukuoka,Japan","institution_ids":["https://openalex.org/I4210099780","https://openalex.org/I4210132370"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32302598,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1940","last_page":"1945"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9782999753952026,"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":0.9782999753952026,"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":0.0024999999441206455,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.002199999988079071,"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/sparse-approximation","display_name":"Sparse approximation","score":0.5224999785423279},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5162000060081482},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5131999850273132},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5019000172615051},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4684000015258789},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4458000063896179},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.43849998712539673},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4287000000476837},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.4171999990940094},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4133000075817108}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7001000046730042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5579000115394592},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5224999785423279},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5162000060081482},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5131999850273132},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5080999732017517},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5019000172615051},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4684000015258789},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4634000062942505},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4458000063896179},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.43849998712539673},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4287000000476837},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.4171999990940094},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4133000075817108},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.4090999960899353},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.38940000534057617},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38659998774528503},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.37380000948905945},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3666999936103821},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.3610000014305115},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C57654395","wikidata":"https://www.wikidata.org/wiki/Q1097775","display_name":"Compression artifact","level":5,"score":0.3359000086784363},{"id":"https://openalex.org/C146044194","wikidata":"https://www.wikidata.org/wiki/Q5157334","display_name":"Computational photography","level":4,"score":0.32670000195503235},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3102000057697296},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.29679998755455017},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2863999903202057},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.2777999937534332},{"id":"https://openalex.org/C198751489","wikidata":"https://www.wikidata.org/wiki/Q2195","display_name":"JPEG","level":3,"score":0.27639999985694885},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.26330000162124634},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.26080000400543213},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.2587999999523163},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.2526000142097473},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipaasc65261.2025.11249070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc65261.2025.11249070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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":9,"referenced_works":["https://openalex.org/W2083020047","https://openalex.org/W2117259536","https://openalex.org/W2118375162","https://openalex.org/W2138692623","https://openalex.org/W2952071070","https://openalex.org/W4244393449","https://openalex.org/W4250955649","https://openalex.org/W4292363360","https://openalex.org/W4408347277"],"related_works":[],"abstract_inverted_index":{"Distributed":[0],"Compressed":[1],"Video":[2],"Sensing":[3],"(DCVS)":[4],"is":[5],"a":[6,129],"video":[7,143],"coding":[8],"framework":[9],"that":[10,132,146],"shifts":[11],"computational":[12],"complexity":[13],"from":[14],"the":[15,18,36,73,91,95,147],"encoder":[16],"to":[17,54,135],"decoder,":[19],"making":[20],"it":[21],"suitable":[22],"for":[23],"low-power":[24],"encoding":[25],"environments.":[26],"Convolutional":[27],"Sparse":[28],"Representation":[29],"(CSR),":[30],"which":[31,78],"models":[32],"an":[33,106],"image":[34,100],"as":[35],"sum":[37],"of":[38,94,109,156],"convolutions":[39],"between":[40],"feature-representing":[41],"dictionary":[42],"filters":[43],"and":[44,58,97,120,158],"their":[45],"corresponding":[46],"sparse":[47],"coefficients,":[48],"has":[49,112],"been":[50,113],"incorporated":[51],"into":[52],"DCVS":[53,130,153],"enhance":[55,136],"reconstruction":[56,137],"quality":[57],"effectively":[59],"suppress":[60],"block":[61],"artifacts.":[62],"However,":[63],"conventional":[64],"CSR":[65,110],"relies":[66],"on":[67,72,141],"convolution":[68],"multiplication":[69],"theorems":[70],"based":[71],"discrete":[74],"Fourier":[75],"transform":[76],"(DFT),":[77],"assumes":[79],"periodic":[80],"boundary":[81,118],"conditions.":[82],"This":[83],"often":[84],"introduces":[85],"artifacts":[86],"near":[87],"signal":[88],"boundaries,":[89],"limiting":[90],"representational":[92,122],"fidelity":[93],"model":[96],"degrading":[98],"overall":[99],"quality.":[101],"To":[102],"address":[103],"this":[104,125],"limitation,":[105],"extended":[107],"form":[108],"(ECSR)":[111],"proposed,":[114],"offering":[115],"more":[116],"flexible":[117],"handling":[119],"improved":[121],"fidelity.":[123],"In":[124],"work,":[126],"we":[127],"present":[128],"method":[131,149],"integrates":[133],"ECSR":[134],"accuracy.":[138],"Experimental":[139],"results":[140],"standard":[142],"datasets":[144],"demonstrate":[145],"proposed":[148],"consistently":[150],"outperforms":[151],"CSR-based":[152],"in":[154],"terms":[155],"PSNR":[157],"SSIM,":[159],"particularly":[160],"under":[161],"low":[162],"compression":[163],"rates.":[164]},"counts_by_year":[],"updated_date":"2025-12-01T00:03:43.161839","created_date":"2025-11-28T00:00:00"}
