{"id":"https://openalex.org/W2755227136","doi":"https://doi.org/10.1109/icip.2017.8296776","title":"Complex nonseparable oversampled lapped transform for sparse representation of millimeter wave radar image","display_name":"Complex nonseparable oversampled lapped transform for sparse representation of millimeter wave radar image","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2755227136","doi":"https://doi.org/10.1109/icip.2017.8296776","mag":"2755227136"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296776","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296776","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5013046400","display_name":"Satoshi Nagayama","orcid":null},"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":false,"raw_author_name":"Satoshi Nagayama","raw_affiliation_strings":["Graduate School of science and Technolozy, Niigata Univ, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of science and Technolozy, Niigata Univ, Japan","institution_ids":["https://openalex.org/I71395657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036282074","display_name":"Shogo M. Ramats","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shogo M. Ramats","raw_affiliation_strings":["Niigata Daigaku, Niigata, Niigata, JP"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Niigata Daigaku, Niigata, Niigata, JP","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051385242","display_name":"Hiroyoshi Yamada","orcid":"https://orcid.org/0000-0002-8861-7229"},"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":false,"raw_author_name":"Hiroyoshi Yamada","raw_affiliation_strings":["Faculty of Engineering, Niigata Univ, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Niigata Univ, Japan","institution_ids":["https://openalex.org/I71395657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003072518","display_name":"Yuuichi S. Giyama","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092470","display_name":"Fujitsu Ten (Japan)","ror":"https://ror.org/00jjgc591","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210092470"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuuichi S. Giyama","raw_affiliation_strings":["FUJITSU TEN LIMITED, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FUJITSU TEN LIMITED, Japan","institution_ids":["https://openalex.org/I4210092470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8759,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.76802508,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2716","last_page":"2720"},"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/T11210","display_name":"Mathematical Analysis and Transform Methods","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9970999956130981,"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/parsevals-theorem","display_name":"Parseval's theorem","score":0.6789411306381226},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.6211890578269958},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5068023800849915},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.506327748298645},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.47288909554481506},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.45919620990753174},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.43373292684555054},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.41610878705978394},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3999677300453186},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3840094208717346},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3587988018989563},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.29499226808547974},{"id":"https://openalex.org/keywords/fractional-fourier-transform","display_name":"Fractional Fourier transform","score":0.16328823566436768},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.13823539018630981},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.11714497208595276}],"concepts":[{"id":"https://openalex.org/C89451469","wikidata":"https://www.wikidata.org/wiki/Q1443036","display_name":"Parseval's theorem","level":5,"score":0.6789411306381226},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.6211890578269958},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5068023800849915},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.506327748298645},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.47288909554481506},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.45919620990753174},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.43373292684555054},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.41610878705978394},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3999677300453186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3840094208717346},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3587988018989563},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.29499226808547974},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.16328823566436768},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.13823539018630981},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.11714497208595276},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296776","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296776","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W340244495","https://openalex.org/W639989723","https://openalex.org/W1481646516","https://openalex.org/W1591116419","https://openalex.org/W1650958574","https://openalex.org/W2018332268","https://openalex.org/W2045369486","https://openalex.org/W2058693698","https://openalex.org/W2116484432","https://openalex.org/W2118799423","https://openalex.org/W2123023890","https://openalex.org/W2171879908","https://openalex.org/W2516327642","https://openalex.org/W2516731600","https://openalex.org/W2547878593","https://openalex.org/W2558879954","https://openalex.org/W4211251910","https://openalex.org/W4300263211"],"related_works":["https://openalex.org/W1522297789","https://openalex.org/W2495194047","https://openalex.org/W2164846160","https://openalex.org/W1983104818","https://openalex.org/W2391387784","https://openalex.org/W2951524812","https://openalex.org/W4298118036","https://openalex.org/W4296137464","https://openalex.org/W2783623030","https://openalex.org/W2889928079"],"abstract_inverted_index":{"This":[0],"work":[1],"generalizes":[2],"an":[3],"existing":[4],"framework":[5],"of":[6,61,83],"nonseparable":[7],"oversampled":[8],"lapped":[9],"transforms":[10],"(NSOLTs)":[11],"to":[12,37,47,65,75],"effectively":[13],"represent":[14],"complex-valued":[15,67],"images.":[16,54,69],"The":[17,32,70,81],"original":[18],"NSOLTs":[19,62],"are":[20],"lattice-structure-based":[21],"redundant":[22],"transforms,":[23],"which":[24],"satisfy":[25],"the":[26,84,90,95],"linear-phase,":[27],"compact-supported":[28],"and":[29,46],"real-valued":[30],"property.":[31],"lattice":[33],"structure":[34,60,85],"is":[35,63,73,86],"able":[36],"constitute":[38],"a":[39,49,58,77,102],"Parseval":[40],"tight":[41],"frame":[42],"with":[43,51],"rational":[44],"redundancy":[45],"generate":[48],"dictionary":[50],"directional":[52],"atomic":[53,68],"In":[55],"this":[56],"study,":[57],"generalized":[59],"proposed":[64],"cover":[66],"novel":[71],"transform":[72],"referred":[74],"as":[76],"complex":[78],"NSOLT":[79],"(CNSOLT).":[80],"effectiveness":[82],"verified":[87],"by":[88],"evaluating":[89],"sparse":[91],"approximation":[92],"performance":[93],"using":[94],"iterative":[96],"hard":[97],"thresholding":[98],"(IHT)":[99],"algorithm":[100],"for":[101],"millimeter":[103],"wave":[104],"radar":[105],"image.":[106]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
