{"id":"https://openalex.org/W4412375053","doi":"https://doi.org/10.1109/access.2025.3587201","title":"A Study on an Improved Generative Adversarial Network Model for Super-Resolution Image Reconstruction","display_name":"A Study on an Improved Generative Adversarial Network Model for Super-Resolution Image Reconstruction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412375053","doi":"https://doi.org/10.1109/access.2025.3587201"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3587201","doi":"https://doi.org/10.1109/access.2025.3587201","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3587201","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3587201","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ximin Qu","orcid":"https://orcid.org/0009-0008-7998-2700","observed_orcids":["https://orcid.org/0009-0008-7998-2700"]},"institutions":[{"id":"https://openalex.org/I1334729051","display_name":"Xinjiang Normal University","ror":"https://ror.org/00ndrvk93","country_code":"CN","type":"education","lineage":["https://openalex.org/I1334729051"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ximin Qu","raw_affiliation_strings":["School of Computer Science and Technology, Xinjiang Normal University, &#x00DC;r&#x00FC;mqi, China"],"raw_orcid":"https://orcid.org/0009-0008-7998-2700","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xinjiang Normal University, &#x00DC;r&#x00FC;mqi, China","institution_ids":["https://openalex.org/I1334729051"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033683260","display_name":"Cheng Peng","orcid":"https://orcid.org/0000-0003-0619-2771","observed_orcids":["https://orcid.org/0000-0003-0619-2771","https://orcid.org/0000-0003-4253-4804","https://orcid.org/0009-0005-1470-4601"]},"institutions":[{"id":"https://openalex.org/I1334729051","display_name":"Xinjiang Normal University","ror":"https://ror.org/00ndrvk93","country_code":"CN","type":"education","lineage":["https://openalex.org/I1334729051"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Peng","raw_affiliation_strings":["School of Computer Science and Technology, Xinjiang Normal University, &#x00DC;r&#x00FC;mqi, China"],"raw_orcid":"https://orcid.org/0000-0003-0619-2771","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xinjiang Normal University, &#x00DC;r&#x00FC;mqi, China","institution_ids":["https://openalex.org/I1334729051"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1334729051"],"apc_list":{"value":2075,"currency":"USD","value_usd":2075},"apc_paid":{"value":2075,"currency":"USD","value_usd":2075},"fwci":0.724,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68565724,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"13","issue":null,"first_page":"119757","last_page":"119771"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9990000128746033,"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":0.9990000128746033,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.00039999998989515007,"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/T11019","display_name":"Image Enhancement Techniques","score":9.999999747378752e-05,"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/image-super-resolution","display_name":"image super-resolution","score":0.9919999837875366},{"id":"https://openalex.org/keywords/srgan","display_name":"SRGAN","score":0.8479999899864197},{"id":"https://openalex.org/keywords/generative-adversarial-networks","display_name":"generative adversarial networks","score":0.9169999957084656},{"id":"https://openalex.org/keywords/convolutional-block-attention-module","display_name":"CBAM","score":0.8569999933242798},{"id":"https://openalex.org/keywords/spectral-normalization","display_name":"spectral normalization","score":0.777999997138977},{"id":"https://openalex.org/keywords/residual-blocks","display_name":"residual blocks","score":0.6890000104904175},{"id":"https://openalex.org/keywords/perceptual-loss","display_name":"perceptual loss","score":0.6919999718666077},{"id":"https://openalex.org/keywords/feature-smoothing","display_name":"feature smoothing","score":0.4000000059604645}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.737611711025238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7194919586181641},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.678013265132904},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.6642274856567383},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5765810608863831},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5590208768844604},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4890523850917816},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4807831645011902},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.416839063167572},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3403303921222687},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2819690704345703}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3587201","doi":"https://doi.org/10.1109/access.2025.3587201","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3587201","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fa8ac6da61734c649f504c7355f3c3ce","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/fa8ac6da61734c649f504c7355f3c3ce","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 119757-119771 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3587201","doi":"https://doi.org/10.1109/access.2025.3587201","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3587201","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1791560514","https://openalex.org/W1930824406","https://openalex.org/W2102166818","https://openalex.org/W2121927366","https://openalex.org/W2133665775","https://openalex.org/W2194775991","https://openalex.org/W2549139847","https://openalex.org/W2607041014","https://openalex.org/W2735224642","https://openalex.org/W2785678896","https://openalex.org/W2891158090","https://openalex.org/W2951559372","https://openalex.org/W2963470893","https://openalex.org/W2964101377","https://openalex.org/W3014337038","https://openalex.org/W4212863985"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W2888032422","https://openalex.org/W2996316059","https://openalex.org/W4410783345","https://openalex.org/W4377980832","https://openalex.org/W2897769091","https://openalex.org/W2845413374","https://openalex.org/W3005996785","https://openalex.org/W3130538189"],"abstract_inverted_index":{"The":[0,57],"SRGAN":[1,44,118],"model":[2,45,119,132],"based":[3],"on":[4,147],"Generative":[5],"Adversarial":[6],"Networks":[7],"(GANs)":[8],"has":[9],"achieved":[10],"breakthroughs":[11],"in":[12,27,62,215],"perceptual":[13],"quality":[14,178],"for":[15,93],"image":[16,212],"super-resolution":[17,145,213],"reconstruction.":[18],"However,":[19],"existing":[20,144],"models":[21],"suffer":[22],"from":[23],"feature":[24,73,86],"smoothing":[25],"effects":[26],"the":[28,34,63,77,94,103,111,117,130,135,148,187,192,209],"generator":[29],"and":[30,75,96,123,141,153,168,183,189,203,218,224],"unstable":[31],"training":[32],"of":[33,116,191,211],"discriminator.":[35],"To":[36],"address":[37],"these":[38],"limitations,":[39],"we":[40,65,89],"propose":[41],"an":[42],"improved":[43],"(denoted":[46],"as":[47,163],"SRGAN-GBDB)":[48],"through":[49,179],"multi-strategy":[50],"collaborative":[51],"optimization":[52,193,201],"to":[53,71,83,105,207],"improve":[54],"reconstruction":[55,121],"quality.":[56,125],"specific":[58],"improvements":[59],"include:":[60],"Firstly,":[61],"generator,":[64],"remove":[66],"batch":[67],"normalization":[68,92],"(BN)":[69],"layers":[70],"alleviate":[72],"degradation":[74],"embed":[76],"Convolutional":[78],"Block":[79],"Attention":[80],"Module":[81],"(CBAM)":[82],"enhance":[84],"high-frequency":[85],"modeling.":[87],"Secondly,":[88],"implement":[90],"spectral":[91],"discriminator":[95,104],"incorporate":[97],"spectrally":[98],"normalized":[99],"residual":[100],"blocks":[101],"into":[102],"strengthen":[106],"its":[107],"discriminative":[108],"capability.":[109],"Additionally,":[110],"joint":[112],"perceptual-adversarial-content":[113],"loss":[114],"function":[115],"balances":[120],"accuracy":[122],"visual":[124,177],"Experimental":[126],"results":[127],"show":[128],"that":[129],"optimized":[131],"SRGAN-GBDB":[133],"outperforms":[134],"traditional":[136],"Bicubic":[137],"interpolation":[138],"method,":[139],"SRGAN,":[140],"several":[142],"other":[143],"algorithms":[146],"Set5,":[149],"Set14,":[150],"BSD100,":[151],"Urban100,":[152],"DIV2K":[154],"datasets.":[155],"It":[156],"not":[157],"only":[158],"improves":[159],"quantitative":[160],"metrics":[161],"such":[162],"PSNR":[164],"(Peak":[165],"Signal-to-Noise":[166],"Ratio)":[167],"SSIM":[169],"(Structural":[170],"Similarity":[171],"Index)":[172],"but":[173],"also":[174],"demonstrates":[175],"superior":[176],"better":[180],"detail":[181],"recovery":[182],"fewer":[184],"artifacts,":[185],"validating":[186],"effectiveness":[188],"superiority":[190],"strategy.":[194],"Future":[195],"work":[196],"will":[197],"explore":[198],"more":[199],"efficient":[200],"methods":[202],"lightweight":[204],"network":[205],"architectures":[206],"facilitate":[208],"application":[210],"systems":[214],"mobile":[216],"platforms":[217],"specialized":[219],"fields":[220],"like":[221],"remote":[222],"sensing":[223],"medical":[225],"imaging.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}
