{"id":"https://openalex.org/W2548354920","doi":"https://doi.org/10.1109/icacci.2016.7732338","title":"Satellite image resolution enhancement using DTCWT and DTCWT based fusion","display_name":"Satellite image resolution enhancement using DTCWT and DTCWT based fusion","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2548354920","doi":"https://doi.org/10.1109/icacci.2016.7732338","mag":"2548354920"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2016.7732338","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5113844271","display_name":"Vineet Vilas Naik","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Vineet Vilas Naik","raw_affiliation_strings":["Department of Electronics and Telecommunication, V.E. S. Institute of Technology, India"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunication, V.E. S. Institute of Technology, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032946968","display_name":"Saylee Gharge","orcid":"https://orcid.org/0000-0002-9387-1707"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Saylee Gharge","raw_affiliation_strings":["Department of Electronics and Telecommunication, V.E. S. Institute of Technology, India"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunication, V.E. S. Institute of Technology, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5113844271"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2918,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.85244302,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1957","last_page":"1962"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9995999932289124,"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":0.9991999864578247,"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/complex-wavelet-transform","display_name":"Complex wavelet transform","score":0.791502833366394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7309490442276001},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.6008605360984802},{"id":"https://openalex.org/keywords/interpolation","display_name":"Interpolation (computer graphics)","score":0.5523548126220703},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5380449295043945},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5100756287574768},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5095982551574707},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.48389801383018494},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4554038941860199},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44501248002052307},{"id":"https://openalex.org/keywords/lanczos-resampling","display_name":"Lanczos resampling","score":0.4427219033241272},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.41364091634750366},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3553485870361328},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.3449852466583252},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.2808492183685303},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.2581796646118164},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.14540451765060425}],"concepts":[{"id":"https://openalex.org/C2777885455","wikidata":"https://www.wikidata.org/wiki/Q5156615","display_name":"Complex wavelet transform","level":5,"score":0.791502833366394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7309490442276001},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.6008605360984802},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.5523548126220703},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5380449295043945},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5100756287574768},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5095982551574707},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.48389801383018494},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4554038941860199},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44501248002052307},{"id":"https://openalex.org/C119256216","wikidata":"https://www.wikidata.org/wiki/Q913012","display_name":"Lanczos resampling","level":3,"score":0.4427219033241272},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.41364091634750366},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3553485870361328},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.3449852466583252},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.2808492183685303},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.2581796646118164},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14540451765060425},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacci.2016.7732338","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2014057517","https://openalex.org/W2020455334","https://openalex.org/W2086633600","https://openalex.org/W2109773745","https://openalex.org/W2114770744","https://openalex.org/W2125837007","https://openalex.org/W2133665775","https://openalex.org/W2136396015","https://openalex.org/W2148770129","https://openalex.org/W2159269332","https://openalex.org/W2162779289","https://openalex.org/W2177031359","https://openalex.org/W4285719527","https://openalex.org/W4394304159","https://openalex.org/W6637925188","https://openalex.org/W6685648643"],"related_works":["https://openalex.org/W2359885256","https://openalex.org/W2331757830","https://openalex.org/W2348426299","https://openalex.org/W3201880405","https://openalex.org/W2547029902","https://openalex.org/W2116037602","https://openalex.org/W2184356407","https://openalex.org/W1940514811","https://openalex.org/W2368671946","https://openalex.org/W2007377145"],"abstract_inverted_index":{"To":[0,28,122,157],"increase":[1],"the":[2,16,24,96,101,112,124,159,162,193,198,201],"resolution":[3,18,36,128,141,153,183],"of":[4,61,65,100,161,178,182,200],"any":[5],"image,":[6,63],"interpolation":[7],"techniques":[8,195],"are":[9,21,26,68,81,89,115,132,144,173,190],"adopted.":[10],"The":[11,86,137,185],"high":[12,69,97,127,140],"frequency":[13,70,83,98],"components":[14],"in":[15],"low":[17,82],"(LR)":[19],"image":[20,35],"lost":[22],"when":[23],"images":[25,129,143,181],"interpolated.":[27],"overcome":[29],"this":[30],"problem":[31],"a":[32,176],"new":[33],"satellite":[34],"enhancement":[37],"algorithm":[38,164],"based":[39,149],"on":[40],"Dual":[41],"Tree":[42],"Complex":[43],"Wavelet":[44],"transform":[45],"(DTCWT)":[46],"and":[47,55,79,119,171,187],"its":[48],"rotated":[49,120],"version":[50],"have":[51],"been":[52],"proposed.":[53],"DTCWT":[54,57,118,148],"Rotated":[56],"give":[58,74,152],"32":[59],"subbands":[60,72,88],"an":[62],"out":[64],"which":[66,73,114],"24":[67],"(HF)":[71],"12":[75],"different":[76],"angular":[77],"information":[78],"8":[80],"(LF)":[84],"subbands.":[85,136],"HF":[87],"interpolated":[90],"by":[91,117],"Lanczos":[92],"Interpolation":[93],"to":[94,110,151,196],"preserve":[95],"contents":[99],"image.":[102,156],"Non":[103],"Local":[104],"Means":[105],"(NLM)":[106],"filtering":[107],"is":[108],"used":[109],"eliminate":[111],"artifacts":[113],"generated":[116],"DTCWT.":[121],"obtain":[123],"two":[125,139],"enhanced":[126,154],"inverse":[130],"transforms":[131],"performed":[133],"over":[134],"respective":[135],"final":[138],"(HR)":[142],"fused":[145],"together":[146],"with":[147,192],"fusion":[150],"HR":[155],"evaluate":[158],"performance":[160,166],"proposed":[163,202],"three":[165],"parameters":[167],"namely":[168],"PSNR,":[169],"SSIM":[170],"Q-Index":[172],"evaluated":[174],"for":[175],"database":[177],"60":[179],"grayscale":[180],"256\u00d7256.":[184],"subjective":[186],"objective":[188],"results":[189],"compared":[191],"existing":[194],"prove":[197],"superiority":[199],"algorithm.":[203]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
