{"id":"https://openalex.org/W2786550750","doi":"https://doi.org/10.1109/apsipa.2017.8282055","title":"Panchromatic and multi-spectral image fusion method based on two-step sparse representation and wavelet transform","display_name":"Panchromatic and multi-spectral image fusion method based on two-step sparse representation and wavelet transform","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2786550750","doi":"https://doi.org/10.1109/apsipa.2017.8282055","mag":"2786550750"},"language":"en","primary_location":{"id":"doi:10.1109/apsipa.2017.8282055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2017.8282055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5024485372","display_name":"Guiqing He","orcid":"https://orcid.org/0000-0001-7267-2373"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guiqing He","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041376155","display_name":"Siyuan Xing","orcid":"https://orcid.org/0000-0003-3874-6521"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyuan Xing","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101128207","display_name":"Dandan Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dandan Dong","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039496980","display_name":"Ximei Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ximei Zhao","raw_affiliation_strings":["Qilu Institute of Technology, Jinan, China"],"affiliations":[{"raw_affiliation_string":"Qilu Institute of Technology, Jinan, China","institution_ids":["https://openalex.org/I152269853"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024485372"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27830365,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":null,"first_page":"259","last_page":"262"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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":1.0,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9955000281333923,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9941999912261963,"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":0.8615108132362366},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.6648505926132202},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6188092231750488},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6063891649246216},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.5927204489707947},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5732412338256836},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5387995839118958},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5281486511230469},{"id":"https://openalex.org/keywords/stationary-wavelet-transform","display_name":"Stationary wavelet transform","score":0.4824598431587219},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.43326008319854736},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.41700854897499084},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4158942401409149},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.4119374752044678},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.41034039855003357},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29269519448280334}],"concepts":[{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.8615108132362366},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.6648505926132202},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6188092231750488},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6063891649246216},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.5927204489707947},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5732412338256836},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5387995839118958},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5281486511230469},{"id":"https://openalex.org/C73339587","wikidata":"https://www.wikidata.org/wiki/Q1375942","display_name":"Stationary wavelet transform","level":5,"score":0.4824598431587219},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.43326008319854736},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.41700854897499084},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4158942401409149},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.4119374752044678},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.41034039855003357},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29269519448280334},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipa.2017.8282055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2017.8282055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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":7,"referenced_works":["https://openalex.org/W2014316959","https://openalex.org/W2037143195","https://openalex.org/W2087964427","https://openalex.org/W2111924917","https://openalex.org/W2114207195","https://openalex.org/W2474462684","https://openalex.org/W2507855991"],"related_works":["https://openalex.org/W2016265625","https://openalex.org/W2111634407","https://openalex.org/W2552089492","https://openalex.org/W4205656132","https://openalex.org/W2008821896","https://openalex.org/W2982240858","https://openalex.org/W2067062989","https://openalex.org/W3004790527","https://openalex.org/W2972860561","https://openalex.org/W634011990"],"abstract_inverted_index":{"Based":[0],"on":[1,19,79],"the":[2,41,45,49,57,61,67,71,74,86,90,99,102,112,119,127,141],"characteristics":[3],"of":[4,11,60,101,131],"two-step":[5,20,34,80],"sparse":[6,21,35,63,75,81,92,96,143,155],"coding":[7,22,82],"and":[8,28,48,65,98,108,145,153],"multi-scale":[9],"analysis":[10,109],"wavelet":[12,29,151],"transform,":[13],"a":[14],"novel":[15],"fusion":[16,159],"algorithm":[17,103],"based":[18,78],"(Two":[23],"Step":[24],"Sparse":[25],"Representation,":[26],"TSSR)":[27],"transform":[30,152],"is":[31,37,83,104,137],"proposed.":[32],"The":[33,134],"strategy":[36],"used":[38],"to":[39,85],"construct":[40],"corresponding":[42],"dictionary":[43],"for":[44],"low-frequency":[46,52],"component":[47,53],"down-":[50],"sampled":[51],"respectively,":[54],"which":[55],"avoids":[56],"training":[58],"process":[59],"traditional":[62,95,142,154],"representation":[64,156],"improves":[66],"computing":[68,135],"speed.":[69],"At":[70],"same":[72],"time,":[73],"coefficient":[76],"solution":[77,93],"closer":[84],"original":[87],"signal":[88],"than":[89,140,150],"one-step":[91],"in":[94],"representation,":[97],"precision":[100],"higher.":[105],"Experimental":[106],"results":[107],"show":[110],"that":[111],"proposed":[113],"method":[114],"can":[115,124],"not":[116],"only":[117],"keep":[118],"spectral":[120],"characteristics,":[121],"but":[122],"also":[123],"effectively":[125],"integrate":[126],"spatial":[128],"detail":[129],"information":[130],"panchromatic":[132],"images.":[133],"time":[136],"much":[138],"faster":[139],"method,":[144],"it":[146],"has":[147],"more":[148],"advantages":[149],"with":[157],"excellent":[158],"effect.":[160]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}