{"id":"https://openalex.org/W4415432680","doi":"https://doi.org/10.1007/s10044-025-01549-z","title":"Integrating spatial and frequency information for Under-Display Camera image restoration","display_name":"Integrating spatial and frequency information for Under-Display Camera image restoration","publication_year":2025,"publication_date":"2025-10-22","ids":{"openalex":"https://openalex.org/W4415432680","doi":"https://doi.org/10.1007/s10044-025-01549-z"},"language":"en","primary_location":{"id":"doi:10.1007/s10044-025-01549-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10044-025-01549-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10044-025-01549-z.pdf","source":{"id":"https://openalex.org/S45497385","display_name":"Pattern Analysis and Applications","issn_l":"1433-7541","issn":["1433-7541","1433-755X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pattern Analysis and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10044-025-01549-z.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042424327","display_name":"Kyusu Ahn","orcid":"https://orcid.org/0009-0008-3548-833X"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Kyusu Ahn","raw_affiliation_strings":["Research Center, Samsung Display Co., Ltd., Yongin, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Center, Samsung Display Co., Ltd., Yongin, Republic of Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006733433","display_name":"Jin-Pyo Kim","orcid":"https://orcid.org/0000-0002-4370-1195"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]},{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I2802457231","display_name":"New Generation University College","ror":"https://ror.org/015aem925","country_code":"ET","type":"education","lineage":["https://openalex.org/I2802457231"]}],"countries":["ET","KR"],"is_corresponding":false,"raw_author_name":"Jinpyo Kim","raw_affiliation_strings":["Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea","Department of Data Science, Seoul National University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Department of Data Science, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I2802457231","https://openalex.org/I139264467","https://openalex.org/I118373667"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101490689","display_name":"Chanwoo Park","orcid":"https://orcid.org/0000-0001-8984-7395"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chanwoo Park","raw_affiliation_strings":["Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100391621","display_name":"Ji-Soo Kim","orcid":"https://orcid.org/0000-0003-1571-4762"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]},{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I2802457231","display_name":"New Generation University College","ror":"https://ror.org/015aem925","country_code":"ET","type":"education","lineage":["https://openalex.org/I2802457231"]}],"countries":["ET","KR"],"is_corresponding":false,"raw_author_name":"JiSoo Kim","raw_affiliation_strings":["Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea","Department of Data Science, Seoul National University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Department of Data Science, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I2802457231","https://openalex.org/I139264467","https://openalex.org/I118373667"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100767182","display_name":"Jaejin Lee","orcid":"https://orcid.org/0000-0003-4638-8170"},"institutions":[{"id":"https://openalex.org/I118373667","display_name":"Seoul National University of Science and Technology","ror":"https://ror.org/00chfja07","country_code":"KR","type":"education","lineage":["https://openalex.org/I118373667"]},{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]},{"id":"https://openalex.org/I2802457231","display_name":"New Generation University College","ror":"https://ror.org/015aem925","country_code":"ET","type":"education","lineage":["https://openalex.org/I2802457231"]}],"countries":["ET","KR"],"is_corresponding":false,"raw_author_name":"Jaejin Lee","raw_affiliation_strings":["Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea","Department of Data Science, Seoul National University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Department of Data Science, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I2802457231","https://openalex.org/I139264467","https://openalex.org/I118373667"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5042424327"],"corresponding_institution_ids":["https://openalex.org/I2250650973"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26368706,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":"4","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/T10531","display_name":"Advanced Vision and Imaging","score":0.9984999895095825,"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":0.9976999759674072,"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/block","display_name":"Block (permutation group theory)","score":0.7199000120162964},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.7174000144004822},{"id":"https://openalex.org/keywords/spatial-frequency","display_name":"Spatial frequency","score":0.5879999995231628},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5230000019073486},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.4968999922275543},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4846999943256378},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4715999960899353},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4221000075340271}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7498000264167786},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.7199000120162964},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.7174000144004822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6898999810218811},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5885000228881836},{"id":"https://openalex.org/C100921725","wikidata":"https://www.wikidata.org/wiki/Q1650811","display_name":"Spatial frequency","level":2,"score":0.5879999995231628},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5230000019073486},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.4968999922275543},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4846999943256378},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4715999960899353},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4221000075340271},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4187999963760376},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.3824000060558319},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.3668999969959259},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3529999852180481},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3156999945640564},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.27630001306533813},{"id":"https://openalex.org/C15336307","wikidata":"https://www.wikidata.org/wiki/Q1766051","display_name":"Lens (geology)","level":2,"score":0.26249998807907104}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10044-025-01549-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10044-025-01549-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10044-025-01549-z.pdf","source":{"id":"https://openalex.org/S45497385","display_name":"Pattern Analysis and Applications","issn_l":"1433-7541","issn":["1433-7541","1433-755X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pattern Analysis and Applications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10044-025-01549-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10044-025-01549-z","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10044-025-01549-z.pdf","source":{"id":"https://openalex.org/S45497385","display_name":"Pattern Analysis and Applications","issn_l":"1433-7541","issn":["1433-7541","1433-755X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pattern Analysis and Applications","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1559343570","display_name":null,"funder_award_id":"4199990214639","funder_id":"https://openalex.org/F4320321292","funder_display_name":"Seoul National University"},{"id":"https://openalex.org/G1821537739","display_name":null,"funder_award_id":"4199990214639","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G2045000886","display_name":null,"funder_award_id":"RS-2023-00222663","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G30685149","display_name":null,"funder_award_id":"BK21 FOUR","funder_id":"https://openalex.org/F4320320671","funder_display_name":"National Research Foundation"},{"id":"https://openalex.org/G8433158499","display_name":null,"funder_award_id":"2018-0-00581","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321292","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320322724","display_name":"Ministry of Education, India","ror":"https://ror.org/048xjjh50"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320332195","display_name":"Samsung","ror":"https://ror.org/04w3jy968"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415432680.pdf","grobid_xml":"https://content.openalex.org/works/W4415432680.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1930824406","https://openalex.org/W2560533888","https://openalex.org/W2884585870","https://openalex.org/W2930755307","https://openalex.org/W2949695917","https://openalex.org/W2963470893","https://openalex.org/W2964101377","https://openalex.org/W3035326127","https://openalex.org/W3100506797","https://openalex.org/W3109494165","https://openalex.org/W3128106819","https://openalex.org/W3128392297","https://openalex.org/W3138516171","https://openalex.org/W3170697543","https://openalex.org/W3175361891","https://openalex.org/W3177152970","https://openalex.org/W3181566645","https://openalex.org/W3202040256","https://openalex.org/W3207918547","https://openalex.org/W4225672218","https://openalex.org/W4283026176","https://openalex.org/W4312654281","https://openalex.org/W4312812783","https://openalex.org/W4321231496","https://openalex.org/W4321231503","https://openalex.org/W4386075642","https://openalex.org/W4386075678","https://openalex.org/W4386075871","https://openalex.org/W4386076463","https://openalex.org/W4387967967","https://openalex.org/W4388430459","https://openalex.org/W4389146874","https://openalex.org/W4389305847","https://openalex.org/W4390872932","https://openalex.org/W4390873480","https://openalex.org/W4390874540","https://openalex.org/W4398763571","https://openalex.org/W4401070625","https://openalex.org/W4406067047","https://openalex.org/W4412885638"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Under-Display":[1],"Camera":[2],"(UDC)":[3],"houses":[4],"a":[5,10,85,129,134],"digital":[6],"camera":[7],"lens":[8],"under":[9],"display":[11],"panel.":[12],"However,":[13],"UDC":[14,34,59],"introduces":[15],"complex":[16],"degradations":[17,60,191],"such":[18,153,166],"as":[19,154,167],"noise,":[20],"blur,":[21,157],"decrease":[22],"in":[23,40,49,61,107,163],"transmittance,":[24],"and":[25,44,65,99,119,139,156,169,179,188,205],"flare.":[26,193],"Despite":[27],"the":[28,41,50,58,62,73,76,108],"remarkable":[29],"progress,":[30],"previous":[31],"research":[32],"on":[33,37,79,150],"mainly":[35],"focuses":[36,148],"eliminating":[38],"diffraction":[39],"spatial":[42,130,178],"domain":[43,131,136],"rarely":[45],"explores":[46],"its":[47],"potential":[48],"frequency":[51,69,135,180],"domain.":[52],"In":[53],"this":[54],"paper,":[55],"we":[56,82],"revisit":[57],"Fourier":[63],"space":[64],"figure":[66],"out":[67],"intrinsic":[68],"priors":[70],"that":[71,91],"imply":[72],"presence":[74],"of":[75,104],"flares.":[77],"Based":[78],"these":[80],"observations,":[81],"propose":[83],"SFIM,":[84],"novel":[86],"multi-level":[87,142],"deep":[88],"neural":[89],"network":[90,127],"efficiently":[92],"restores":[93],"UDC-distorted":[94],"images":[95],"by":[96],"integrating":[97],"local":[98,117],"global":[100,124],"(the":[101],"collective":[102],"contribution":[103],"all":[105],"points":[106],"image)":[109],"information.":[110],"SFIM":[111],"uses":[112],"CNNs":[113],"to":[114,122,174],"capture":[115],"fine-grained":[116],"details":[118],"FFT-based":[120],"models":[121],"extract":[123],"patterns.":[125],"The":[126],"comprises":[128],"block":[132,137,144],"(SDB),":[133],"(FDB),":[138],"an":[140],"attention-based":[141],"integration":[143],"(AMIB).":[145],"Specifically,":[146],"SDB":[147],"more":[149],"detailed":[151],"textures":[152],"noise":[155],"FDB":[158],"emphasizes":[159],"irregular":[160,190],"texture":[161],"loss":[162],"extensive":[164],"areas":[165],"flare,":[168],"AMIB":[170],"employs":[171],"cross-domain":[172],"attention":[173],"selectively":[175],"integrate":[176],"complementary":[177],"features":[181],"across":[182],"multiple":[183],"levels,":[184],"enhancing":[185],"detail":[186],"recovery":[187],"mitigating":[189],"like":[192],"SFIM\u2019s":[194],"superior":[195],"performance":[196],"over":[197],"state-of-the-art":[198],"approaches":[199],"is":[200,211],"demonstrated":[201],"through":[202],"rigorous":[203],"quantitative":[204],"qualitative":[206],"assessments.":[207],"Our":[208],"source":[209],"code":[210],"publicly":[212],"available":[213],"at:":[214],"https://github.com/mcrl/SFIM":[215],".":[216]},"counts_by_year":[],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-24T00:00:00"}
