{"id":"https://openalex.org/W2014496189","doi":"https://doi.org/10.1109/icoin.2015.7057914","title":"New interpolation method based on combination of Discrete cosine transform and wavelet transform","display_name":"New interpolation method based on combination of Discrete cosine transform and wavelet transform","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2014496189","doi":"https://doi.org/10.1109/icoin.2015.7057914","mag":"2014496189"},"language":"en","primary_location":{"id":"doi:10.1109/icoin.2015.7057914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icoin.2015.7057914","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Information Networking (ICOIN)","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/A5042600174","display_name":"Ramesh Kumar Lama","orcid":null},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Ramesh Kumar Lama","raw_affiliation_strings":["Dept. Information and Communication Engineering, Chosun University, Gwangju, Korea","Dept. Information and Communication Engineering, Chosun University, 375 Seosuk-Dong, Dong-Gu, Gwangju 501-759, Korea"],"affiliations":[{"raw_affiliation_string":"Dept. Information and Communication Engineering, Chosun University, Gwangju, Korea","institution_ids":["https://openalex.org/I152238500"]},{"raw_affiliation_string":"Dept. Information and Communication Engineering, Chosun University, 375 Seosuk-Dong, Dong-Gu, Gwangju 501-759, Korea","institution_ids":["https://openalex.org/I152238500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049515671","display_name":"Goo\u2010Rak Kwon","orcid":"https://orcid.org/0000-0003-3486-8812"},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Goo-Rak Kwon","raw_affiliation_strings":["Dept. Information and Communication Engineering, Chosun University, Gwangju, Korea","Dept. Information and Communication Engineering, Chosun University, 375 Seosuk-Dong, Dong-Gu, Gwangju 501-759, Korea"],"affiliations":[{"raw_affiliation_string":"Dept. Information and Communication Engineering, Chosun University, Gwangju, Korea","institution_ids":["https://openalex.org/I152238500"]},{"raw_affiliation_string":"Dept. Information and Communication Engineering, Chosun University, 375 Seosuk-Dong, Dong-Gu, Gwangju 501-759, Korea","institution_ids":["https://openalex.org/I152238500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5042600174"],"corresponding_institution_ids":["https://openalex.org/I152238500"],"apc_list":null,"apc_paid":null,"fwci":0.9205,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.81871629,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"10","issue":null,"first_page":"363","last_page":"366"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9997000098228455,"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":0.9991000294685364,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.8646240234375},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.724895715713501},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.6166069507598877},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5684537291526794},{"id":"https://openalex.org/keywords/stationary-wavelet-transform","display_name":"Stationary wavelet transform","score":0.5593346953392029},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5503057837486267},{"id":"https://openalex.org/keywords/second-generation-wavelet-transform","display_name":"Second-generation wavelet transform","score":0.5478399395942688},{"id":"https://openalex.org/keywords/lapped-transform","display_name":"Lapped transform","score":0.5380451679229736},{"id":"https://openalex.org/keywords/discrete-sine-transform","display_name":"Discrete sine transform","score":0.5123804807662964},{"id":"https://openalex.org/keywords/harmonic-wavelet-transform","display_name":"Harmonic wavelet transform","score":0.5096285343170166},{"id":"https://openalex.org/keywords/peak-signal-to-noise-ratio","display_name":"Peak signal-to-noise ratio","score":0.4823598265647888},{"id":"https://openalex.org/keywords/s-transform","display_name":"S transform","score":0.47622424364089966},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46104830503463745},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4464327394962311},{"id":"https://openalex.org/keywords/transform-coding","display_name":"Transform coding","score":0.4449917674064636},{"id":"https://openalex.org/keywords/modified-discrete-cosine-transform","display_name":"Modified discrete cosine transform","score":0.4180123209953308},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4027758538722992},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.359932541847229},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.32084333896636963},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.16673314571380615},{"id":"https://openalex.org/keywords/fractional-fourier-transform","display_name":"Fractional Fourier transform","score":0.16568470001220703},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.09986162185668945},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.051219046115875244}],"concepts":[{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.8646240234375},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.724895715713501},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.6166069507598877},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5684537291526794},{"id":"https://openalex.org/C73339587","wikidata":"https://www.wikidata.org/wiki/Q1375942","display_name":"Stationary wavelet transform","level":5,"score":0.5593346953392029},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5503057837486267},{"id":"https://openalex.org/C111350171","wikidata":"https://www.wikidata.org/wiki/Q7443700","display_name":"Second-generation wavelet transform","level":5,"score":0.5478399395942688},{"id":"https://openalex.org/C91458471","wikidata":"https://www.wikidata.org/wiki/Q17096468","display_name":"Lapped transform","level":5,"score":0.5380451679229736},{"id":"https://openalex.org/C167058841","wikidata":"https://www.wikidata.org/wiki/Q971039","display_name":"Discrete sine transform","level":5,"score":0.5123804807662964},{"id":"https://openalex.org/C1109138","wikidata":"https://www.wikidata.org/wiki/Q3280930","display_name":"Harmonic wavelet transform","level":5,"score":0.5096285343170166},{"id":"https://openalex.org/C154579607","wikidata":"https://www.wikidata.org/wiki/Q3373850","display_name":"Peak signal-to-noise ratio","level":3,"score":0.4823598265647888},{"id":"https://openalex.org/C99234102","wikidata":"https://www.wikidata.org/wiki/Q7395403","display_name":"S transform","level":5,"score":0.47622424364089966},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46104830503463745},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4464327394962311},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.4449917674064636},{"id":"https://openalex.org/C28726691","wikidata":"https://www.wikidata.org/wiki/Q1268231","display_name":"Modified discrete cosine transform","level":5,"score":0.4180123209953308},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4027758538722992},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.359932541847229},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.32084333896636963},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.16673314571380615},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.16568470001220703},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.09986162185668945},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.051219046115875244}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icoin.2015.7057914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icoin.2015.7057914","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Information Networking (ICOIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2023404078","https://openalex.org/W2038677069","https://openalex.org/W2065628492","https://openalex.org/W2113524221","https://openalex.org/W2116337048","https://openalex.org/W2163423121","https://openalex.org/W2172128189","https://openalex.org/W6683752055"],"related_works":["https://openalex.org/W2090071970","https://openalex.org/W2162505377","https://openalex.org/W2963134360","https://openalex.org/W2978563117","https://openalex.org/W2946386739","https://openalex.org/W2128618986","https://openalex.org/W2903035460","https://openalex.org/W2036363614","https://openalex.org/W1964500914","https://openalex.org/W1500725064"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,47],"propose":[4],"an":[5],"image":[6,29,62],"interpolation":[7],"algorithm":[8],"that":[9],"uses":[10,21],"a":[11],"hybrid":[12,85],"transform":[13,20,38],"and":[14,72,94],"zero":[15],"padding":[16],"scheme.":[17],"The":[18,60,76],"proposed":[19,84],"the":[22,28,35,44,53,66,73,80,83],"Discrete":[23,36],"Wavelet":[24],"Transform":[25],"to":[26,42,51],"decompose":[27],"into":[30],"multi":[31],"resolution":[32],"subbands":[33],"where":[34],"cosine":[37],"(DCT)":[39],"is":[40,63],"used":[41],"interpolate":[43,52],"image.":[45,75],"Then":[46],"use":[48],"Zeropadding":[49],"method":[50,86],"DCT":[54],"transformed":[55],"high":[56],"frequency":[57],"wavelet":[58],"coefficients.":[59],"upscaled":[61],"generated":[64],"using":[65],"inverse":[67],"DWT":[68],"of":[69,82,89],"interpolated":[70],"coefficients":[71],"original":[74],"experimental":[77],"results":[78],"demonstrate":[79],"efficiency":[81],"in":[87],"terms":[88],"peak":[90],"signal-to-noise":[91],"ratio":[92],"PSNR":[93],"visual":[95],"quality.":[96]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
