{"id":"https://openalex.org/W2945235635","doi":"https://doi.org/10.1145/3316551.3318234","title":"A Novel Method for Single Infrared Dim Small Target Detection Based on ROI extraction and Matrix Recovery","display_name":"A Novel Method for Single Infrared Dim Small Target Detection Based on ROI extraction and Matrix Recovery","publication_year":2019,"publication_date":"2019-02-24","ids":{"openalex":"https://openalex.org/W2945235635","doi":"https://doi.org/10.1145/3316551.3318234","mag":"2945235635"},"language":"en","primary_location":{"id":"doi:10.1145/3316551.3318234","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3316551.3318234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5005273133","display_name":"Bin Xiong","orcid":"https://orcid.org/0000-0002-9960-903X"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Xiong","raw_affiliation_strings":["School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108577371","display_name":"Xinhan Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinhan Huang","raw_affiliation_strings":["School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100749649","display_name":"Min Wang","orcid":"https://orcid.org/0000-0003-1756-1405"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Wang","raw_affiliation_strings":["School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"95","last_page":"99"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11856","display_name":"Thermography and Photoacoustic Techniques","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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-science","display_name":"Computer science","score":0.6501144170761108},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6175069808959961},{"id":"https://openalex.org/keywords/region-of-interest","display_name":"Region of interest","score":0.5623147487640381},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5533292293548584},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5031086802482605},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4977579414844513},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4918327331542969},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.49157389998435974},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45308366417884827},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.42604267597198486}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6501144170761108},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6175069808959961},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.5623147487640381},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5533292293548584},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5031086802482605},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4977579414844513},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4918327331542969},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.49157389998435974},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45308366417884827},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.42604267597198486},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3316551.3318234","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3316551.3318234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1736339626","https://openalex.org/W1978993121","https://openalex.org/W1992873714","https://openalex.org/W2004580922","https://openalex.org/W2041560658","https://openalex.org/W2045352990","https://openalex.org/W2058928435","https://openalex.org/W2065784426","https://openalex.org/W2070582667","https://openalex.org/W2087670735","https://openalex.org/W2139356527","https://openalex.org/W2145962650"],"related_works":["https://openalex.org/W2380927352","https://openalex.org/W3178621026","https://openalex.org/W2367227827","https://openalex.org/W2137598809","https://openalex.org/W2045983409","https://openalex.org/W2950161005","https://openalex.org/W2028998628","https://openalex.org/W2967273010","https://openalex.org/W2788769272","https://openalex.org/W2951544014"],"abstract_inverted_index":{"Low-rank":[0],"and":[1,31,59,74,98,120,131],"sparse":[2,132],"matrix":[3,60,133],"recovery":[4,61],"method":[5,42,113,127],"based":[6,52,128],"on":[7,53,129],"Robust":[8],"Principal":[9],"Component":[10],"Analysis":[11],"(RPCA)":[12],"model":[13],"are":[14],"widely":[15],"used":[16],"in":[17,33],"infrared":[18,44],"small":[19,46],"target":[20,47,91,101],"detection.":[21],"In":[22],"order":[23],"to":[24,89],"solve":[25],"the":[26,65,76,100,111,117],"problem":[27],"of":[28,55,71,124],"time":[29,119],"consuming":[30],"difficulty":[32],"parameter":[34],"selection":[35],"when":[36],"using":[37,102],"this":[38],"method,":[39],"a":[40],"novel":[41],"for":[43],"dim":[45],"detection":[48,126],"under":[49],"complex":[50],"background":[51],"Region":[54],"Interest":[56],"(ROI)":[57],"extraction":[58],"is":[62],"presented.":[63],"Calculate":[64],"Variance":[66],"Weighted":[67],"Information":[68],"Entropy":[69],"(VWIE)":[70],"every":[72],"sub-block":[73],"extract":[75],"ROI":[77],"firstly;":[78],"then":[79],"use":[80],"Adaptive":[81],"Parameter":[82],"Inexact":[83],"Augmented":[84],"Lagrange":[85],"Multiplier":[86],"(APIALM)":[87],"algorithm":[88],"recover":[90],"image":[92],"from":[93],"extracted":[94],"ROI;":[95],"finally":[96],"segmenting":[97],"calibrating":[99],"an":[103],"adaptive":[104],"threshold":[105],"method.":[106],"Experiments":[107],"results":[108],"demonstrate":[109],"that":[110],"proposed":[112],"can":[114],"significantly":[115],"decline":[116],"running":[118],"retain":[121],"most":[122],"properties":[123],"traditional":[125],"low-rank":[130],"recovery.":[134]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
