{"id":"https://openalex.org/W2153037214","doi":"https://doi.org/10.1109/iscas.2013.6572002","title":"Separation of weak reflection from a single superimposed image using gradient profile sharpness","display_name":"Separation of weak reflection from a single superimposed image using gradient profile sharpness","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W2153037214","doi":"https://doi.org/10.1109/iscas.2013.6572002","mag":"2153037214"},"language":"en","primary_location":{"id":"doi:10.1109/iscas.2013.6572002","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2013.6572002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Symposium on Circuits and Systems (ISCAS2013)","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/A5101842274","display_name":"Qing Yan","orcid":"https://orcid.org/0000-0003-4118-200X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qing Yan","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, CN"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, CN","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101225921","display_name":"Yi Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Xu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, CN"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, CN","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067044466","display_name":"Xiaokang Yang","orcid":"https://orcid.org/0000-0003-4029-3322"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaokang Yang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, CN"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, CN","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101842274"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.2722,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.63307489,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"937","last_page":"940"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9998000264167786,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9998000264167786,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9995999932289124,"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/T11569","display_name":"Optical Coherence Tomography Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/computer-vision","display_name":"Computer vision","score":0.7101373672485352},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6640675067901611},{"id":"https://openalex.org/keywords/reflection","display_name":"Reflection (computer programming)","score":0.6459072828292847},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6032698750495911},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5606597661972046},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5412338376045227},{"id":"https://openalex.org/keywords/image-gradient","display_name":"Image gradient","score":0.5181499719619751},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.4960533082485199},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4790957272052765},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.430406391620636},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4273640513420105},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4187844395637512},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.41420239210128784},{"id":"https://openalex.org/keywords/feature-detection","display_name":"Feature detection (computer vision)","score":0.3893333673477173},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3607594966888428},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3405337929725647},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2908870279788971},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.255434513092041},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24930837750434875},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11406815052032471},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.10751950740814209}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7101373672485352},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6640675067901611},{"id":"https://openalex.org/C65682993","wikidata":"https://www.wikidata.org/wiki/Q1056451","display_name":"Reflection (computer programming)","level":2,"score":0.6459072828292847},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6032698750495911},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5606597661972046},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5412338376045227},{"id":"https://openalex.org/C182037307","wikidata":"https://www.wikidata.org/wiki/Q17039097","display_name":"Image gradient","level":5,"score":0.5181499719619751},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.4960533082485199},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4790957272052765},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.430406391620636},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4273640513420105},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4187844395637512},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.41420239210128784},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.3893333673477173},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3607594966888428},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3405337929725647},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2908870279788971},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.255434513092041},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24930837750434875},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11406815052032471},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.10751950740814209},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas.2013.6572002","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2013.6572002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Symposium on Circuits and Systems (ISCAS2013)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1558369361","https://openalex.org/W1716765157","https://openalex.org/W1844192772","https://openalex.org/W2036379242","https://openalex.org/W2099847307","https://openalex.org/W2100140302","https://openalex.org/W2107530646","https://openalex.org/W2112668648","https://openalex.org/W2116086749","https://openalex.org/W2122122766","https://openalex.org/W2123132941","https://openalex.org/W2131020910","https://openalex.org/W2157862498","https://openalex.org/W6633270728","https://openalex.org/W6637748566"],"related_works":["https://openalex.org/W2312819198","https://openalex.org/W3036032503","https://openalex.org/W4383560752","https://openalex.org/W4280622786","https://openalex.org/W2561491196","https://openalex.org/W3087840940","https://openalex.org/W2319500318","https://openalex.org/W2610832043","https://openalex.org/W4312753625","https://openalex.org/W2356662304"],"abstract_inverted_index":{"It":[0],"is":[1,98],"a":[2,8,55,68,73,84,91,111,142],"massively":[3],"ill-posed":[4],"problem":[5],"to":[6,48,82,124,133,146],"separate":[7],"superimposed":[9,57,93],"image":[10,14,22,108,154],"into":[11],"an":[12,20,126],"object":[13,18,117,153],"of":[15,23,63,70,87,103],"our":[16,177],"interested":[17],"and":[19,100,155],"interference":[21,107,157],"reflection.":[24],"Previous":[25],"studies":[26],"relied":[27],"on":[28],"redundant":[29],"information":[30],"introduced":[31],"by":[32,129],"multiple":[33],"exposure":[34],"or":[35,72,187],"multi-view":[36],"configurations":[37],"in":[38,51,168],"the":[39,60,96,105,116,148,152,156,164,169],"separation.":[40,171],"Later":[41],"some":[42],"new":[43],"methods":[44,65],"proposed":[45],"tailor-made":[46],"constraints":[47],"remove":[49],"reflection":[50,89,97],"specific":[52],"conditions":[53],"for":[54,90],"single":[56,92],"image.":[58,94,118,158],"However,":[59],"separated":[61],"results":[62,174,183],"these":[64],"always":[66,101],"have":[67,110],"lot":[69],"residuals":[71],"few":[74],"tone":[75],"distortions.":[76,189],"In":[77],"this":[78,121],"paper,":[79],"we":[80,140],"aim":[81],"realize":[83],"clear":[85],"separation":[86,128,182],"weak":[88,99],"Since":[95],"out":[102],"focus,":[104],"resulted":[106],"would":[109],"smoother":[112],"edge":[113],"map":[114],"than":[115],"We":[119],"utilize":[120],"smoothness":[122],"constraint":[123],"obtain":[125],"initial":[127,170],"classifying":[130],"gradients":[131,166],"according":[132],"GPS":[134],"(gradient":[135],"profile":[136],"sharpness)":[137],"computation.":[138],"Then":[139],"propose":[141],"gradient":[143],"validation":[144],"framework":[145,160],"reduce":[147],"structural":[149],"correlation":[150],"between":[151],"This":[159],"can":[161,179],"well":[162],"correct":[163],"misclassified":[165],"obtained":[167],"The":[172],"experimental":[173],"demonstrate":[175],"that":[176],"method":[178],"generate":[180],"promising":[181],"with":[184],"little":[185],"residual":[186],"color":[188]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
