{"id":"https://openalex.org/W4386598417","doi":"https://doi.org/10.1109/icip49359.2023.10222374","title":"Variational Deep Atmospheric Turbulence Correction for Video","display_name":"Variational Deep Atmospheric Turbulence Correction for Video","publication_year":2023,"publication_date":"2023-09-11","ids":{"openalex":"https://openalex.org/W4386598417","doi":"https://doi.org/10.1109/icip49359.2023.10222374"},"language":"en","primary_location":{"id":"doi:10.1109/icip49359.2023.10222374","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip49359.2023.10222374","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Image Processing (ICIP)","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/A5046773255","display_name":"Santiago L\u00f3pez-Tapia","orcid":"https://orcid.org/0000-0003-2090-7446"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Santiago L\u00f3pez-Tapia","raw_affiliation_strings":["Northwestern University,Dept. of Electrical and Computer Engineering,Evanston,IL,USA","Dept. of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern University,Dept. of Electrical and Computer Engineering,Evanston,IL,USA","institution_ids":["https://openalex.org/I111979921"]},{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053465205","display_name":"Xijun Wang","orcid":"https://orcid.org/0000-0001-9155-7653"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xijun Wang","raw_affiliation_strings":["Northwestern University,Dept. of Electrical and Computer Engineering,Evanston,IL,USA","Dept. of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern University,Dept. of Electrical and Computer Engineering,Evanston,IL,USA","institution_ids":["https://openalex.org/I111979921"]},{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048650003","display_name":"Aggelos K. Katsaggelos","orcid":"https://orcid.org/0000-0003-4554-0070"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aggelos K. Katsaggelos","raw_affiliation_strings":["Northwestern University,Dept. of Electrical and Computer Engineering,Evanston,IL,USA","Dept. of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern University,Dept. of Electrical and Computer Engineering,Evanston,IL,USA","institution_ids":["https://openalex.org/I111979921"]},{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I111979921"],"apc_list":null,"apc_paid":null,"fwci":0.4855,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.7249637,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9980000257492065,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9962999820709229,"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/autoencoder","display_name":"Autoencoder","score":0.7743703126907349},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6999901533126831},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.628653883934021},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6009929180145264},{"id":"https://openalex.org/keywords/atmospheric-turbulence","display_name":"Atmospheric turbulence","score":0.5583726167678833},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5180190205574036},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5126089453697205},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5005748271942139},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4944887161254883},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.4612957239151001},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.45772963762283325},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45692917704582214},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4482482075691223},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4322674870491028},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.403812974691391},{"id":"https://openalex.org/keywords/turbulence","display_name":"Turbulence","score":0.3413631319999695},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32002532482147217},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22858905792236328},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.1946539580821991},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08886626362800598},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07721534371376038}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7743703126907349},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6999901533126831},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.628653883934021},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6009929180145264},{"id":"https://openalex.org/C3019432306","wikidata":"https://www.wikidata.org/wiki/Q190132","display_name":"Atmospheric turbulence","level":3,"score":0.5583726167678833},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5180190205574036},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5126089453697205},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5005748271942139},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4944887161254883},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.4612957239151001},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.45772963762283325},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45692917704582214},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4482482075691223},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4322674870491028},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.403812974691391},{"id":"https://openalex.org/C196558001","wikidata":"https://www.wikidata.org/wiki/Q190132","display_name":"Turbulence","level":2,"score":0.3413631319999695},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32002532482147217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22858905792236328},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.1946539580821991},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08886626362800598},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07721534371376038},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip49359.2023.10222374","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icip49359.2023.10222374","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.47999998927116394}],"awards":[],"funders":[{"id":"https://openalex.org/F4320312530","display_name":"Office of the Director of National Intelligence","ror":"https://ror.org/01v3fsc55"},{"id":"https://openalex.org/F4320333051","display_name":"Intelligence Advanced Research Projects Activity","ror":"https://ror.org/01v3fsc55"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1968698674","https://openalex.org/W2081927794","https://openalex.org/W2126926806","https://openalex.org/W2476548250","https://openalex.org/W2586894204","https://openalex.org/W2953823547","https://openalex.org/W2962814024","https://openalex.org/W2963774720","https://openalex.org/W2964277374","https://openalex.org/W3101187320","https://openalex.org/W3157704539","https://openalex.org/W3183800428","https://openalex.org/W3193593975","https://openalex.org/W4224313400","https://openalex.org/W4225672218","https://openalex.org/W4283310858","https://openalex.org/W4307647699","https://openalex.org/W4312305207","https://openalex.org/W4312617714","https://openalex.org/W6726497184","https://openalex.org/W6780226713"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W4386815338","https://openalex.org/W2145836866","https://openalex.org/W2368553989"],"abstract_inverted_index":{"This":[0,40],"paper":[1],"presents":[2],"a":[3,17,29,51,75,101],"novel":[4],"variational":[5,30,52],"deep-learning":[6],"approach":[7],"for":[8,94],"video":[9,23,96,104],"atmospheric":[10],"turbulence":[11],"correction.":[12],"We":[13],"modify":[14],"and":[15,38,88,109,115],"tailor":[16],"Nonlinear":[18],"Activation":[19],"Free":[20],"Network":[21],"to":[22,70,120],"restoration.":[24],"By":[25],"including":[26],"it":[27],"in":[28],"inference":[31],"framework,":[32],"we":[33,56],"boost":[34],"the":[35,45,62,65,71,80,85,89,95,107,112],"model\u2019s":[36],"performance":[37],"stability.":[39],"is":[41],"achieved":[42],"through":[43],"conditioning":[44],"model":[46],"on":[47,79,100],"features":[48,59],"extracted":[49],"by":[50,60],"autoencoder":[53],"(VAE).":[54],"Furthermore,":[55],"enhance":[57],"these":[58],"making":[61],"encoder":[63],"of":[64,82,84,111],"VAE":[66],"include":[67],"information":[68],"pertinent":[69],"image":[72],"formation":[73],"via":[74],"new":[76],"loss":[77],"based":[78],"prediction":[81],"parameters":[83],"geometrical":[86],"distortion":[87],"spatially":[90],"variant":[91],"blur":[92],"responsible":[93],"sequence":[97],"degradation.":[98],"Experiments":[99],"comprehensive":[102],"synthetic":[103],"dataset":[105],"demonstrate":[106],"effectiveness":[108],"reliability":[110],"proposed":[113],"method":[114],"validate":[116],"its":[117],"superiority":[118],"compared":[119],"existing":[121],"state-of-the-art":[122],"approaches.":[123]},"counts_by_year":[{"year":2024,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}