{"id":"https://openalex.org/W2583700394","doi":"https://doi.org/10.1109/icinfa.2016.7832096","title":"Morphological component decomposition combined with compressed sensing for image compression","display_name":"Morphological component decomposition combined with compressed sensing for image compression","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2583700394","doi":"https://doi.org/10.1109/icinfa.2016.7832096","mag":"2583700394"},"language":"en","primary_location":{"id":"doi:10.1109/icinfa.2016.7832096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icinfa.2016.7832096","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Information and Automation (ICIA)","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/A5101604890","display_name":"Xuan Zhu","orcid":"https://orcid.org/0000-0003-1838-3583"},"institutions":[{"id":"https://openalex.org/I37802460","display_name":"Northwest University","ror":"https://ror.org/00z3td547","country_code":"CN","type":"education","lineage":["https://openalex.org/I37802460"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuan Zhu","raw_affiliation_strings":["School of Information Science and Technology, Northwest University, Xi'an, Shaanxi Province, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Northwest University, Xi'an, Shaanxi Province, China","institution_ids":["https://openalex.org/I37802460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418917","display_name":"Li Liu","orcid":"https://orcid.org/0000-0003-3331-093X"},"institutions":[{"id":"https://openalex.org/I37802460","display_name":"Northwest University","ror":"https://ror.org/00z3td547","country_code":"CN","type":"education","lineage":["https://openalex.org/I37802460"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Liu","raw_affiliation_strings":["School of Information Science and Technology, Northwest University, Xi'an, Shaanxi Province, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Northwest University, Xi'an, Shaanxi Province, China","institution_ids":["https://openalex.org/I37802460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101485542","display_name":"Peng Jin","orcid":"https://orcid.org/0000-0002-5163-9686"},"institutions":[{"id":"https://openalex.org/I37802460","display_name":"Northwest University","ror":"https://ror.org/00z3td547","country_code":"CN","type":"education","lineage":["https://openalex.org/I37802460"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Jin","raw_affiliation_strings":["School of Information Science and Technology, Northwest University, Xi'an, Shaanxi Province, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Northwest University, Xi'an, Shaanxi Province, China","institution_ids":["https://openalex.org/I37802460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057520965","display_name":"Na Ai","orcid":null},"institutions":[{"id":"https://openalex.org/I37802460","display_name":"Northwest University","ror":"https://ror.org/00z3td547","country_code":"CN","type":"education","lineage":["https://openalex.org/I37802460"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na Ai","raw_affiliation_strings":["School of Information Science and Technology, Northwest University, Xi'an, Shaanxi Province, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Northwest University, Xi'an, Shaanxi Province, China","institution_ids":["https://openalex.org/I37802460"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101604890"],"corresponding_institution_ids":["https://openalex.org/I37802460"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.23303155,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2016","issue":null,"first_page":"1726","last_page":"1731"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9998999834060669,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9998999834060669,"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":0.9995999932289124,"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7898368835449219},{"id":"https://openalex.org/keywords/contourlet","display_name":"Contourlet","score":0.7154498100280762},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6571760177612305},{"id":"https://openalex.org/keywords/texture-compression","display_name":"Texture compression","score":0.6200951337814331},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.615513801574707},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.6026557087898254},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5620762705802917},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5487762093544006},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.5224548578262329},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.48514923453330994},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4781035780906677},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.4603848457336426},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.4597731828689575},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.45338332653045654},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44553685188293457},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.23881256580352783},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.05205598473548889}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7898368835449219},{"id":"https://openalex.org/C20479862","wikidata":"https://www.wikidata.org/wiki/Q5165589","display_name":"Contourlet","level":4,"score":0.7154498100280762},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6571760177612305},{"id":"https://openalex.org/C54243161","wikidata":"https://www.wikidata.org/wiki/Q39333","display_name":"Texture compression","level":5,"score":0.6200951337814331},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.615513801574707},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.6026557087898254},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5620762705802917},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5487762093544006},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.5224548578262329},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.48514923453330994},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4781035780906677},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.4603848457336426},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.4597731828689575},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.45338332653045654},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44553685188293457},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.23881256580352783},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.05205598473548889},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icinfa.2016.7832096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icinfa.2016.7832096","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Information and Automation (ICIA)","raw_type":"proceedings-article"},{"id":"mag:2753618463","is_oa":false,"landing_page_url":"http://jglobal.jst.go.jp/en/public/20090422/201702220173306938","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W207373900","https://openalex.org/W1560910787","https://openalex.org/W2005212372","https://openalex.org/W2010961420","https://openalex.org/W2024164329","https://openalex.org/W2032182503","https://openalex.org/W2036493455","https://openalex.org/W2055846072","https://openalex.org/W2079860279","https://openalex.org/W2083936177","https://openalex.org/W2087345335","https://openalex.org/W2114147096","https://openalex.org/W2140856955","https://openalex.org/W2145096794","https://openalex.org/W2148685281","https://openalex.org/W2154846263","https://openalex.org/W2195586549","https://openalex.org/W2267048413","https://openalex.org/W2296616510","https://openalex.org/W2349288466","https://openalex.org/W2377802547","https://openalex.org/W2381483169","https://openalex.org/W2409616175","https://openalex.org/W4250955649","https://openalex.org/W6608410706","https://openalex.org/W6653633566"],"related_works":["https://openalex.org/W2161332283","https://openalex.org/W2166724105","https://openalex.org/W1983661653","https://openalex.org/W2093957690","https://openalex.org/W2003873690","https://openalex.org/W2165772202","https://openalex.org/W2144602437","https://openalex.org/W2115502907","https://openalex.org/W2261167768","https://openalex.org/W1981609904"],"abstract_inverted_index":{"Basing":[0],"on":[1],"the":[2,5,26,30,34,38,40,46,53,57,68,72,93,99,103,118,124],"fact":[3],"that":[4],"cartoon":[6,47,55,95,125],"and":[7,32,48,62,66,81,96,114,122,127],"texture":[8,70,128],"in":[9],"one":[10],"image":[11,87],"have":[12],"different":[13],"morphological":[14],"characteristics,":[15],"we":[16,51],"propose":[17],"a":[18],"new":[19,104],"method":[20,105],"to":[21],"compress":[22],"image.":[23],"Combining":[24],"RDWT,":[25],"dictionary":[27,35],"sparsely":[28,36],"representing":[29,37],"cartoon,":[31],"WAT,":[33],"texture,":[39],"presented":[41],"model":[42],"can":[43],"effectively":[44],"obtain":[45],"texture.":[49,97],"Then,":[50],"reconstruct":[52,67],"compressed":[54,69,94],"by":[56,71,91],"combination":[58,73],"of":[59,74],"Contourlet":[60],"Transform":[61],"Compressed":[63,82],"Sensing":[64,83],"(CS)":[65],"single":[75],"layer":[76],"discrete":[77],"wavelet":[78],"transform":[79],"(SL-DWT)":[80],"(CS).":[84],"The":[85],"reconstructed":[86],"will":[88],"be":[89],"obtained":[90],"superposing":[92],"As":[98],"experimental":[100],"results":[101],"show,":[102],"has":[106,132],"good":[107],"performances":[108],"for":[109],"preserving":[110],"large":[111],"scale":[112],"structure":[113],"mainly":[115],"details":[116],"under":[117],"low":[119],"sampling":[120],"rate,":[121],"ensuring":[123],"completion":[126],"clear.":[129],"Moreover,":[130],"it":[131],"higher":[133],"compression":[134],"rates.":[135]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}