{"id":"https://openalex.org/W2049127998","doi":"https://doi.org/10.1109/vcip.2014.7051493","title":"Re-weighting the morphological diversity","display_name":"Re-weighting the morphological diversity","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W2049127998","doi":"https://doi.org/10.1109/vcip.2014.7051493","mag":"2049127998"},"language":"en","primary_location":{"id":"doi:10.1109/vcip.2014.7051493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2014.7051493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Visual Communications and Image Processing Conference","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/A5088682683","display_name":"Guan\u2010Ju Peng","orcid":"https://orcid.org/0000-0001-5508-9485"},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]},{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Guan-Ju Peng","raw_affiliation_strings":["Academia Sinica, Institute of Information Science, Taiwan","Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei?115, Taiwan"],"affiliations":[{"raw_affiliation_string":"Academia Sinica, Institute of Information Science, Taiwan","institution_ids":["https://openalex.org/I4210098366"]},{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei?115, Taiwan","institution_ids":["https://openalex.org/I84653119"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058554535","display_name":"Wen-Liang Hwang","orcid":"https://orcid.org/0000-0002-5546-6575"},"institutions":[{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]},{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wen-Liang Hwang","raw_affiliation_strings":["Academia Sinica, Institute of Information Science, Taiwan","Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei?115, Taiwan"],"affiliations":[{"raw_affiliation_string":"Academia Sinica, Institute of Information Science, Taiwan","institution_ids":["https://openalex.org/I4210098366"]},{"raw_affiliation_string":"Institute of Information Science, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei?115, Taiwan","institution_ids":["https://openalex.org/I84653119"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088682683"],"corresponding_institution_ids":["https://openalex.org/I4210098366","https://openalex.org/I84653119"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1148528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"17","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9975000023841858,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9975000023841858,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9932000041007996,"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/inpainting","display_name":"Inpainting","score":0.8322475552558899},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6933752298355103},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5906288623809814},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5710358023643494},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5163268446922302},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.5091378092765808},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.4994657039642334},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.46753212809562683},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.4629247188568115},{"id":"https://openalex.org/keywords/mutual-coherence","display_name":"Mutual coherence","score":0.4589989185333252},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4564100205898285},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4231325685977936},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3584569990634918},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24717554450035095},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2063479721546173},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09533348679542542}],"concepts":[{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.8322475552558899},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6933752298355103},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5906288623809814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5710358023643494},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5163268446922302},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.5091378092765808},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.4994657039642334},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.46753212809562683},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.4629247188568115},{"id":"https://openalex.org/C45900066","wikidata":"https://www.wikidata.org/wiki/Q6944191","display_name":"Mutual coherence","level":3,"score":0.4589989185333252},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4564100205898285},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4231325685977936},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3584569990634918},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24717554450035095},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2063479721546173},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09533348679542542},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip.2014.7051493","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip.2014.7051493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Visual Communications and Image Processing Conference","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":7,"referenced_works":["https://openalex.org/W1560910787","https://openalex.org/W1980929117","https://openalex.org/W1981337995","https://openalex.org/W1999905919","https://openalex.org/W2010641531","https://openalex.org/W2146482778","https://openalex.org/W2154996879"],"related_works":["https://openalex.org/W2380775572","https://openalex.org/W2213520135","https://openalex.org/W2244018504","https://openalex.org/W4242046654","https://openalex.org/W3174923100","https://openalex.org/W3134074939","https://openalex.org/W204290405","https://openalex.org/W2461069268","https://openalex.org/W2068941797","https://openalex.org/W2059311958"],"abstract_inverted_index":{"Signal":[0],"separation":[1,108],"has":[2,30],"a":[3,35,111],"fundamental":[4],"role":[5],"in":[6,34,60,94],"many":[7],"image":[8],"applications,":[9],"such":[10],"as":[11],"noise":[12],"removing":[13],"(white":[14],"noise,":[15],"reflection,":[16],"rain,":[17],"etc),":[18],"segmentation,":[19],"and":[20,81],"inpainting.":[21],"To":[22],"fulfill":[23],"signal":[24,107],"separation,":[25],"morphological":[26],"component":[27],"analysis":[28],"(MCA)":[29],"been":[31],"widely":[32],"deployed":[33],"plenty":[36],"of":[37,48,74],"applications":[38],"[1],":[39],"[2],":[40],"[3].":[41],"MCA":[42,75],"uses":[43],"dictionaries":[44,54],"to":[45,86],"model":[46],"morphologies":[47],"subcomponents,":[49],"but":[50],"the":[51,57,61,71,77,91,95,105],"coherence":[52],"between":[53],"may":[55],"cause":[56],"defect":[58,92],"presenting":[59,93],"obtained":[62,96],"subcomponents":[63,97],"[4],":[64],"[5].":[65],"In":[66],"this":[67],"article,":[68],"we":[69],"replace":[70],"sparse":[72,79],"coding":[73],"with":[76],"weighted":[78],"coding,":[80],"by":[82],"assigning":[83],"heavier":[84],"weights":[85],"dictionaries'":[87],"highly":[88],"coherent":[89],"atoms,":[90],"is":[98],"reduced.":[99],"The":[100],"experimental":[101],"results":[102],"show":[103],"that":[104],"proposed":[106],"algorithm":[109],"achieves":[110],"significant":[112],"performance":[113],"gain":[114],"over":[115],"MCA.":[116]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}