{"id":"https://openalex.org/W4389538640","doi":"https://doi.org/10.1109/tci.2023.3340617","title":"Dual-Stream Adaptive Convergent Low-Light Image Enhancement Network Based on Frequency Perception","display_name":"Dual-Stream Adaptive Convergent Low-Light Image Enhancement Network Based on Frequency Perception","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4389538640","doi":"https://doi.org/10.1109/tci.2023.3340617"},"language":"en","primary_location":{"id":"doi:10.1109/tci.2023.3340617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2023.3340617","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2334-0118","2573-0436"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Imaging","raw_type":"journal-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/A5071370650","display_name":"Guang Han","orcid":"https://orcid.org/0000-0003-4812-9180"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guang Han","raw_affiliation_strings":["School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-4812-9180","affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101599198","display_name":"Kang Wu","orcid":"https://orcid.org/0009-0000-6317-7741"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang Wu","raw_affiliation_strings":["School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0000-6317-7741","affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086740899","display_name":"Fanyu Zeng","orcid":"https://orcid.org/0000-0002-4883-5096"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fanyu Zeng","raw_affiliation_strings":["School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-4883-5096","affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081669641","display_name":"Jixin Liu","orcid":"https://orcid.org/0000-0001-8414-4199"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jixin Liu","raw_affiliation_strings":["School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-8414-4199","affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008386708","display_name":"Sam Kwong","orcid":"https://orcid.org/0000-0001-7484-7261"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sam Kwong","raw_affiliation_strings":["Department of Computing and Decision Science, Lingnan University, Hong Kong","Department of Computing and Decision Science, Lingnan University, New Territories, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7484-7261","affiliations":[{"raw_affiliation_string":"Department of Computing and Decision Science, Lingnan University, Hong Kong","institution_ids":[]},{"raw_affiliation_string":"Department of Computing and Decision Science, Lingnan University, New Territories, Hong Kong","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2763,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.82687053,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"1152","last_page":"1164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement 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/T11019","display_name":"Image Enhancement 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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9990000128746033,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.996999979019165,"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/computer-science","display_name":"Computer science","score":0.7452272772789001},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7306250333786011},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6006592512130737},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.5854060053825378},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5501851439476013},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4695226550102234},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.42490923404693604},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.41208508610725403},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12789762020111084}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7452272772789001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7306250333786011},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6006592512130737},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5854060053825378},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5501851439476013},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4695226550102234},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.42490923404693604},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41208508610725403},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12789762020111084},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tci.2023.3340617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2023.3340617","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2334-0118","2573-0436"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1996021349","https://openalex.org/W2025328853","https://openalex.org/W2076205488","https://openalex.org/W2114770744","https://openalex.org/W2254039850","https://openalex.org/W2331128040","https://openalex.org/W2566376500","https://openalex.org/W2783399029","https://openalex.org/W2799396445","https://openalex.org/W2893333553","https://openalex.org/W2897662688","https://openalex.org/W2948354154","https://openalex.org/W2962785568","https://openalex.org/W2962974533","https://openalex.org/W2963466723","https://openalex.org/W2963767233","https://openalex.org/W2981718299","https://openalex.org/W2981847167","https://openalex.org/W2983873691","https://openalex.org/W2989045104","https://openalex.org/W3026169246","https://openalex.org/W3033529678","https://openalex.org/W3034895805","https://openalex.org/W3035731588","https://openalex.org/W3096609285","https://openalex.org/W3100618669","https://openalex.org/W3106912575","https://openalex.org/W3107113662","https://openalex.org/W3120540810","https://openalex.org/W3121661546","https://openalex.org/W3159250660","https://openalex.org/W3176663332","https://openalex.org/W3185888870","https://openalex.org/W3202418656","https://openalex.org/W3203605797","https://openalex.org/W3207918547","https://openalex.org/W4225672218","https://openalex.org/W4226334005","https://openalex.org/W4283837736","https://openalex.org/W4308238078","https://openalex.org/W4312156328","https://openalex.org/W4312812783","https://openalex.org/W4318767589","https://openalex.org/W4319998010","https://openalex.org/W4320000919","https://openalex.org/W4366493140","https://openalex.org/W4383751869","https://openalex.org/W4385245566","https://openalex.org/W4386076325","https://openalex.org/W4387967967","https://openalex.org/W6755037456","https://openalex.org/W6779163297","https://openalex.org/W6784333009","https://openalex.org/W6788135285","https://openalex.org/W6797578546","https://openalex.org/W7046367878"],"related_works":["https://openalex.org/W2601157893","https://openalex.org/W2131735617","https://openalex.org/W2373006798","https://openalex.org/W2056912418","https://openalex.org/W2123759770","https://openalex.org/W2033213769","https://openalex.org/W2811390910","https://openalex.org/W4312376745","https://openalex.org/W2082269393","https://openalex.org/W2043960970"],"abstract_inverted_index":{"Low-light":[0],"image":[1,195,237],"enhancement":[2,238],"is":[3,92,110,136,229],"a":[4,44,72,106,199],"crucial":[5],"area":[6],"of":[7,98,127,133,143,202,235],"research":[8],"in":[9,40,52,57,61,101,239],"computer":[10,240],"vision,":[11],"aimed":[12],"at":[13,145],"recovering":[14],"normally":[15],"exposed":[16],"images":[17,20],"from":[18],"low-light":[19,236],"to":[21,94,112,116,138,160,183,231],"facilitate":[22],"high-level":[23],"vision":[24],"tasks":[25],"such":[26],"as":[27],"target":[28],"detection,":[29],"tracking,":[30],"and":[31,121,164,177,217,228],"recognition.":[32],"However,":[33],"the":[34,53,62,86,99,102,113,123,128,140,150,167,180,185,191,206,210,233],"convolutional":[35],"neural":[36],"networks":[37],"commonly":[38],"used":[39,93],"this":[41,67,69],"field":[42,234],"have":[43],"bias":[45],"towards":[46],"extracting":[47],"low-frequency":[48,134,181],"local":[49],"structural":[50,141],"features":[51,135,144,163,173,182],"spatial":[54],"domain,":[55],"resulting":[56],"unclear":[58],"texture":[59,196],"details":[60],"enhanced":[63,194],"images.":[64],"To":[65],"address":[66],"limitation,":[68],"paper":[70],"proposes":[71],"novel":[73],"frequency-domain":[74],"perception-based":[75],"model,":[76],"called":[77],"DSFPNet.":[78],"This":[79],"model":[80,95,152,192,213,224],"has":[81],"three":[82,168],"unique":[83],"features.":[84],"First,":[85],"recursive":[87],"The":[88,171,223],"Hadamard":[89],"product":[90],"method":[91],"long-range":[96],"relationships":[97],"Transformer":[100],"feature":[103],"extraction.":[104],"Second,":[105],"bilateral":[107],"gating":[108],"mechanism":[109],"added":[111,137],"feedforward":[114],"network":[115],"filter":[117],"out":[118],"useless":[119],"information":[120],"improve":[122],"nonlinear":[124],"modeling":[125],"capability":[126],"module.":[129],"Third,":[130],"cross-layer":[131],"connectivity":[132],"maintain":[139],"stability":[142],"different":[146],"levels.":[147],"In":[148],"addition,":[149],"proposed":[151,211],"uses":[153],"an":[154],"EFF":[155],"(Enhancing":[156],"Frequency":[157],"Features)":[158],"module":[159],"extract":[161],"frequency":[162,187],"selectively":[165],"fuse":[166],"high":[169],"frequencies.":[170],"fused":[172],"are":[174],"then":[175],"aligned":[176],"reconstructed":[178],"with":[179],"obtain":[184],"final":[186],"features,":[188],"which":[189],"helps":[190],"recover":[193],"details.":[197],"Through":[198],"large":[200],"number":[201],"experimental":[203],"results":[204],"on":[205],"two":[207],"public":[208],"datasets,":[209],"DSFPNet":[212],"shows":[214],"excellent":[215],"performances":[216],"outperforms":[218],"many":[219],"existing":[220],"state-of-the-art":[221],"methods.":[222],"exhibits":[225],"good":[226],"potential":[227],"expected":[230],"advance":[232],"vision.":[241]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
