{"id":"https://openalex.org/W2069680281","doi":"https://doi.org/10.1109/ispacs.2013.6704610","title":"Iterative PCA approach for blind restoration of single blurred image","display_name":"Iterative PCA approach for blind restoration of single blurred image","publication_year":2013,"publication_date":"2013-11-01","ids":{"openalex":"https://openalex.org/W2069680281","doi":"https://doi.org/10.1109/ispacs.2013.6704610","mag":"2069680281"},"language":"en","primary_location":{"id":"doi:10.1109/ispacs.2013.6704610","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs.2013.6704610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Symposium on Intelligent Signal Processing and Communication Systems","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/A5100863804","display_name":"Ryotaro Nakamura","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Ryotaro Nakamura","raw_affiliation_strings":["School of Integrated Design Engineering, Keio University, Yokohama, Japan"],"affiliations":[{"raw_affiliation_string":"School of Integrated Design Engineering, Keio University, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020657583","display_name":"Yasue Mitsukura","orcid":"https://orcid.org/0000-0001-5575-8589"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yasue Mitsukura","raw_affiliation_strings":["Department of System Design Engineering, Keio University, Yokohama, Japan","Department of Syst. Design Eng., Keio Univ., Yokohama, Japan"],"affiliations":[{"raw_affiliation_string":"Department of System Design Engineering, Keio University, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"Department of Syst. Design Eng., Keio Univ., Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105504673","display_name":"Nozomu Hamada","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nozomu Hamada","raw_affiliation_strings":["Keio University, Yokohama, Japan","Keio University,, Yokohama, Japan"],"affiliations":[{"raw_affiliation_string":"Keio University, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"Keio University,, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100863804"],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.5443,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.7107438,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"543","last_page":"546"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9983000159263611,"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/image-restoration","display_name":"Image restoration","score":0.751480221748352},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6797197461128235},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6291693449020386},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6227015852928162},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6163893938064575},{"id":"https://openalex.org/keywords/iterative-and-incremental-development","display_name":"Iterative and incremental development","score":0.5020887851715088},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4894753694534302},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4355868697166443},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4190841317176819},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4157181680202484},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40686842799186707},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3816038966178894},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.25162094831466675}],"concepts":[{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.751480221748352},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6797197461128235},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6291693449020386},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6227015852928162},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6163893938064575},{"id":"https://openalex.org/C143587482","wikidata":"https://www.wikidata.org/wiki/Q1543216","display_name":"Iterative and incremental development","level":2,"score":0.5020887851715088},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4894753694534302},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4355868697166443},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4190841317176819},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4157181680202484},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40686842799186707},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3816038966178894},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.25162094831466675},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","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/ispacs.2013.6704610","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispacs.2013.6704610","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Symposium on Intelligent Signal Processing and Communication Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1970958080","https://openalex.org/W2017927102","https://openalex.org/W2088909704","https://openalex.org/W2126252886","https://openalex.org/W2133700636","https://openalex.org/W2138451337","https://openalex.org/W2161566109","https://openalex.org/W2170608748","https://openalex.org/W2540180983","https://openalex.org/W6679452560"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W1549363203","https://openalex.org/W4231274751","https://openalex.org/W2154063878","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W1518215897","https://openalex.org/W1566995892","https://openalex.org/W2152370264"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,28,90],"single-channel":[4],"image":[5],"blind":[6,25],"restoration":[7,26,91,102],"using":[8],"iterative":[9,77],"principal":[10],"components":[11,39,71],"analysis":[12],"(PCA)":[13],"to":[14,66,89,100],"improve":[15,65,101],"the":[16,34,68,80,118,124,135],"quality":[17,103],"of":[18,30,36,56,93],"restoration.":[19],"Previously":[20],"proposed":[21,85,125],"PCA":[22,78],"approaches":[23],"for":[24],"have":[27,114],"lot":[29],"problems.":[31],"For":[32,109],"example,":[33],"process":[35],"boosting":[37],"high-frequency":[38],"would":[40],"be":[41],"improvable,":[42],"no":[43],"numerical":[44],"evaluation":[45],"has":[46],"been":[47,74,115],"performed,":[48],"and":[49,97],"etc.":[50],"Generating":[51],"an":[52],"ensemble":[53],"by":[54],"means":[55],"Gaussian":[57],"filter":[58],"application,":[59],"discussed":[60],"in":[61,104],"this":[62],"paper,":[63],"could":[64],"extract":[67],"high":[69,81],"frequency":[70,82],"which":[72],"had":[73],"lost.":[75],"Furthermore,":[76],"boosts":[79],"components.":[83],"Our":[84],"method":[86,126],"is":[87],"applied":[88],"example":[92],"atmospheric":[94],"turbulence-degraded":[95],"imagery,":[96],"we":[98,120],"verified":[99],"comparisons":[105],"with":[106],"conventional":[107,136],"methods.":[108,137],"demonstrating":[110],"comparative":[111],"experiments,":[112],"simulations":[113],"conducted.":[116],"From":[117],"results,":[119],"can":[121],"confirm":[122],"that":[123],"gives":[127],"higher":[128],"PSNR":[129],"as":[130,132],"well":[131],"SSIM":[133],"than":[134]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
