{"id":"https://openalex.org/W4402916095","doi":"https://doi.org/10.1109/icip51287.2024.10648195","title":"A Cnn-Transformer Network Based Snr Guided High Frequency Reconstruction for Low Light Image Enhancement","display_name":"A Cnn-Transformer Network Based Snr Guided High Frequency Reconstruction for Low Light Image Enhancement","publication_year":2024,"publication_date":"2024-09-27","ids":{"openalex":"https://openalex.org/W4402916095","doi":"https://doi.org/10.1109/icip51287.2024.10648195"},"language":"en","primary_location":{"id":"doi:10.1109/icip51287.2024.10648195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip51287.2024.10648195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","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/A5100405898","display_name":"Jin Zhang","orcid":"https://orcid.org/0000-0001-5462-3631"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jin Zhang","raw_affiliation_strings":["Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010131867","display_name":"Haiyan Jin","orcid":"https://orcid.org/0000-0003-3742-4029"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haiyan Jin","raw_affiliation_strings":["Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089049162","display_name":"Haonan Su","orcid":"https://orcid.org/0000-0002-5481-1082"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haonan Su","raw_affiliation_strings":["Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046450643","display_name":"Yuanlin Zhang","orcid":"https://orcid.org/0000-0003-0960-3636"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuanlin Zhang","raw_affiliation_strings":["Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045601614","display_name":"Zhaolin Xiao","orcid":"https://orcid.org/0000-0003-2457-5944"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhaolin Xiao","raw_affiliation_strings":["Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066874244","display_name":"Bin Wang","orcid":"https://orcid.org/0000-0002-6311-5185"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bin Wang","raw_affiliation_strings":["Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Technology,Faculty of Computer Science and Engineering","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100405898"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.548,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.74995975,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1649","last_page":"1655"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14158","display_name":"Optical Systems and Laser Technology","score":0.9911999702453613,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9868999719619751,"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-science","display_name":"Computer science","score":0.6593839526176453},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5779518485069275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5241161584854126},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.49161607027053833},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4734596610069275},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41527092456817627},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.1716916263103485},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11183184385299683},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.07565122842788696}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6593839526176453},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5779518485069275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5241161584854126},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.49161607027053833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4734596610069275},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41527092456817627},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.1716916263103485},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11183184385299683},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.07565122842788696}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip51287.2024.10648195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip51287.2024.10648195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Image Processing (ICIP)","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":23,"referenced_works":["https://openalex.org/W2003884262","https://openalex.org/W2097073572","https://openalex.org/W2123799082","https://openalex.org/W2566376500","https://openalex.org/W2780108394","https://openalex.org/W2783573276","https://openalex.org/W3034347506","https://openalex.org/W3034539499","https://openalex.org/W3094502228","https://openalex.org/W3100618669","https://openalex.org/W3121661546","https://openalex.org/W3125869362","https://openalex.org/W3174792937","https://openalex.org/W4226157755","https://openalex.org/W4312249431","https://openalex.org/W4312725970","https://openalex.org/W4313059954","https://openalex.org/W4313547876","https://openalex.org/W4372259883","https://openalex.org/W4382240242","https://openalex.org/W4389473889","https://openalex.org/W6637373629","https://openalex.org/W6754146604"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Photographs":[0],"taken":[1],"in":[2,25,41,94,137,158],"low-light":[3,17],"conditions":[4],"have":[5],"a":[6,20,26,50,85,124],"low":[7,59,72],"signal-to-noise":[8,22],"ratio":[9],"and":[10,32,71,98,115,129,147,162],"impaired":[11],"visual":[12],"quality.":[13],"We":[14],"observe":[15],"that":[16,151],"images":[18,101],"exhibit":[19],"lower":[21],"ratio,":[23],"resulting":[24,93],"mixture":[27],"of":[28,117,126,142,160],"fine":[29],"details,":[30],"textures,":[31],"noise,":[33],"making":[34],"it":[35],"challenging":[36],"to":[37],"reconstruct":[38],"small-scale":[39],"textures":[40,116],"the":[42,108,113,118,134,138,143],"image.":[43,144],"Inspired":[44],"by":[45,75,84,107],"this":[46],"observation,":[47],"we":[48],"propose":[49],"SNR-guided":[51],"CNN-Transformer":[52],"network":[53],"for":[54],"high":[55,139],"frequency":[56,73,140],"restoration":[57],"during":[58],"light":[60],"image":[61,68,76,81],"enhancement.":[62],"The":[63,79,145],"proposed":[64,153],"method":[65,154],"first":[66],"decomposes":[67],"into":[69],"high-frequency":[70,119],"components":[74,120,141],"decomposition":[77],"module.":[78],"low-frequency":[80,109],"is":[82],"processed":[83],"trainable":[86],"Low":[87],"Frequency":[88],"SNR":[89,110],"Perception":[90],"(LFSP)":[91],"module,":[92],"excellent":[95],"denoising":[96],"performance":[97],"generating":[99],"SNR-enhanced":[100],"with":[102],"clearer":[103],"edge":[104],"contours.":[105],"Guided":[106],"feature":[111],"maps,":[112],"details":[114],"are":[121],"enhanced":[122],"using":[123],"combination":[125],"transformer":[127],"networks":[128],"convolutional":[130],"networks,":[131],"thereby":[132],"compensating":[133],"detail":[135,161],"distortions":[136],"subjective":[146],"objective":[148],"experiments":[149],"demonstrate":[150],"our":[152],"outperforms":[155],"existing":[156],"approaches":[157],"terms":[159],"structure":[163],"preservation.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
