{"id":"https://openalex.org/W2171879908","doi":"https://doi.org/10.1109/icassp.2014.6854075","title":"Structured dictionary learning with 2-D non-separable oversampled lapped transform","display_name":"Structured dictionary learning with 2-D non-separable oversampled lapped transform","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2171879908","doi":"https://doi.org/10.1109/icassp.2014.6854075","mag":"2171879908"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2014.6854075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6854075","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 Acoustics, Speech and Signal Processing (ICASSP)","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/A5070966533","display_name":"Shogo Muramatsu","orcid":"https://orcid.org/0000-0002-2990-1238"},"institutions":[{"id":"https://openalex.org/I71395657","display_name":"Niigata University","ror":"https://ror.org/04ww21r56","country_code":"JP","type":"education","lineage":["https://openalex.org/I71395657"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shogo Muramatsu","raw_affiliation_strings":["Dept. of Electrical and Electronic Eng., Niigata University, Nishi-ku, Niigata, JAPAN"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Electronic Eng., Niigata University, Nishi-ku, Niigata, JAPAN","institution_ids":["https://openalex.org/I71395657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5070966533"],"corresponding_institution_ids":["https://openalex.org/I71395657"],"apc_list":null,"apc_paid":null,"fwci":3.1538,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.91265813,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"54","issue":null,"first_page":"2624","last_page":"2628"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9993000030517578,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9993000030517578,"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/upsampling","display_name":"Upsampling","score":0.7863754034042358},{"id":"https://openalex.org/keywords/parsevals-theorem","display_name":"Parseval's theorem","score":0.7154465317726135},{"id":"https://openalex.org/keywords/lapped-transform","display_name":"Lapped transform","score":0.7090330719947815},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.6401394605636597},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.5894309282302856},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.529426634311676},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5263422727584839},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4844503402709961},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45002418756484985},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4424419403076172},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.43826133012771606},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.4106651246547699},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3525782823562622},{"id":"https://openalex.org/keywords/transform-coding","display_name":"Transform coding","score":0.3395282030105591},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.2393825352191925},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.12707334756851196},{"id":"https://openalex.org/keywords/fractional-fourier-transform","display_name":"Fractional Fourier transform","score":0.11508089303970337}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.7863754034042358},{"id":"https://openalex.org/C89451469","wikidata":"https://www.wikidata.org/wiki/Q1443036","display_name":"Parseval's theorem","level":5,"score":0.7154465317726135},{"id":"https://openalex.org/C91458471","wikidata":"https://www.wikidata.org/wiki/Q17096468","display_name":"Lapped transform","level":5,"score":0.7090330719947815},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.6401394605636597},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.5894309282302856},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.529426634311676},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5263422727584839},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4844503402709961},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45002418756484985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4424419403076172},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.43826133012771606},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.4106651246547699},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3525782823562622},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.3395282030105591},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.2393825352191925},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.12707334756851196},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.11508089303970337},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2014.6854075","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2014.6854075","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 Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W18046889","https://openalex.org/W340244495","https://openalex.org/W562372631","https://openalex.org/W1481646516","https://openalex.org/W1574645113","https://openalex.org/W1591116419","https://openalex.org/W1658679052","https://openalex.org/W1890834058","https://openalex.org/W1964219813","https://openalex.org/W1978961441","https://openalex.org/W1999174140","https://openalex.org/W2024177389","https://openalex.org/W2045328647","https://openalex.org/W2073417610","https://openalex.org/W2086655182","https://openalex.org/W2097719548","https://openalex.org/W2099321050","https://openalex.org/W2100860054","https://openalex.org/W2106002835","https://openalex.org/W2115429828","https://openalex.org/W2115755118","https://openalex.org/W2116148865","https://openalex.org/W2117853853","https://openalex.org/W2119436754","https://openalex.org/W2123023890","https://openalex.org/W2128659236","https://openalex.org/W2134524318","https://openalex.org/W2145404165","https://openalex.org/W2149282631","https://openalex.org/W2149309436","https://openalex.org/W2156923285","https://openalex.org/W2160547390","https://openalex.org/W2163398148","https://openalex.org/W2196956961","https://openalex.org/W2293318283","https://openalex.org/W2296399167","https://openalex.org/W2963322354","https://openalex.org/W4235713725","https://openalex.org/W4254546220","https://openalex.org/W4300263211","https://openalex.org/W4302067267"],"related_works":["https://openalex.org/W3142097109","https://openalex.org/W2138702206","https://openalex.org/W2151738694","https://openalex.org/W3140834049","https://openalex.org/W2978563117","https://openalex.org/W2169808749","https://openalex.org/W1908108260","https://openalex.org/W2556691706","https://openalex.org/W2000728570","https://openalex.org/W2046080157"],"abstract_inverted_index":{"This":[0],"work":[1],"proposes":[2],"a":[3,8,17,22,32,37],"novel":[4],"design":[5],"method":[6,93,118],"of":[7,27,40,73,76,102,115,125],"two-dimensional":[9],"(2-D)":[10],"Non-Separable":[11],"Oversampled":[12],"Lapped":[13],"Transform":[14],"(NSOLT)":[15],"for":[16],"given":[18],"image":[19,111],"by":[20,70,121],"introducing":[21],"typical":[23],"two":[24],"stage":[25],"procedure":[26],"dictionary":[28,39,88,127],"learning.":[29],"NSOLT":[30],"is":[31,67,94,100,119],"lattice-structure-based":[33],"transform":[34],"and":[35,49,79,128],"yields":[36],"redundant":[38],"which":[41],"atoms":[42],"satisfy":[43],"the":[44,54,64,71,74,80,86,91,116],"non-separable,":[45],"symmetric,":[46],"real-valued,":[47],"overlapping":[48],"compact-support":[50],"property.":[51],"In":[52],"addition,":[53],"Parseval":[55],"tight":[56],"frame":[57],"constraint":[58],"can":[59],"structurally":[60],"be":[61],"imposed,":[62],"while":[63],"redundancy":[65],"R":[66],"flexibly":[68],"controlled":[69],"ratio":[72,82],"number":[75],"channels":[77],"P":[78],"downsampling":[81],"M.":[83],"Compared":[84],"with":[85],"other":[87],"learning":[89],"approaches,":[90],"proposed":[92,117],"moderately":[95],"structured":[96],"so":[97],"that":[98],"it":[99],"capable":[101],"multiscale":[103],"construction":[104],"as":[105,107],"well":[106],"atom":[108],"termination":[109],"at":[110],"boundary.":[112],"The":[113],"significance":[114],"verified":[120],"showing":[122],"an":[123],"example":[124],"learned":[126],"sparse":[129],"approximation":[130],"results.":[131]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
