{"id":"https://openalex.org/W4385731862","doi":"https://doi.org/10.1109/tnnls.2023.3300099","title":"HSGAN: Hyperspectral Reconstruction From RGB Images With Generative Adversarial Network","display_name":"HSGAN: Hyperspectral Reconstruction From RGB Images With Generative Adversarial Network","publication_year":2023,"publication_date":"2023-08-10","ids":{"openalex":"https://openalex.org/W4385731862","doi":"https://doi.org/10.1109/tnnls.2023.3300099","pmid":"https://pubmed.ncbi.nlm.nih.gov/37561623"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3300099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3300099","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5071193469","display_name":"Yuzhi Zhao","orcid":"https://orcid.org/0000-0001-8561-2206"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuzhi Zhao","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-8561-2206","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038133707","display_name":"Lai-Man Po","orcid":"https://orcid.org/0000-0002-5185-1492"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Lai-Man Po","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-5185-1492","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102779964","display_name":"Tingyu Lin","orcid":"https://orcid.org/0009-0008-9825-686X"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tingyu Lin","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong"],"raw_orcid":"https://orcid.org/0009-0008-9825-686X","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101842275","display_name":"Qiong Yan","orcid":"https://orcid.org/0009-0003-2942-267X"},"institutions":[{"id":"https://openalex.org/I2800762105","display_name":"Shatin Hospital","ror":"https://ror.org/037s3ck33","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I1294586568","https://openalex.org/I2800762105"]},{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiong Yan","raw_affiliation_strings":["SenseTime Research and Tetras.AI, Shatin, Hong Kong","SenseTime Research and Tetras.AI, Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Research and Tetras.AI, Shatin, Hong Kong","institution_ids":["https://openalex.org/I2800762105"]},{"raw_affiliation_string":"SenseTime Research and Tetras.AI, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109629691","display_name":"Wei Liu","orcid":"https://orcid.org/0009-0006-0914-9620"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["ByteDance, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ByteDance, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015022081","display_name":"Pengfei Xian","orcid":"https://orcid.org/0000-0001-5632-7780"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Pengfei Xian","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-5632-7780","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5946,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.93709487,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"35","issue":"12","first_page":"17137","last_page":"17150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9997000098228455,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991999864578247,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7903969883918762},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7690733075141907},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.7648311853408813},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7274712920188904},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6602784395217896},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5965073108673096},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5555593371391296},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5248539447784424},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5145963430404663},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43618834018707275},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.43203508853912354},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4294106960296631},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13054043054580688}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7903969883918762},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7690733075141907},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.7648311853408813},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7274712920188904},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6602784395217896},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5965073108673096},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5555593371391296},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5248539447784424},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5145963430404663},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43618834018707275},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.43203508853912354},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4294106960296631},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13054043054580688},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3300099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3300099","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37561623","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37561623","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":90,"referenced_works":["https://openalex.org/W8423413","https://openalex.org/W1550575628","https://openalex.org/W1901129140","https://openalex.org/W1965061537","https://openalex.org/W1979216741","https://openalex.org/W1984915255","https://openalex.org/W1985051078","https://openalex.org/W1996473670","https://openalex.org/W1996607671","https://openalex.org/W2002498099","https://openalex.org/W2010319424","https://openalex.org/W2012946078","https://openalex.org/W2015264016","https://openalex.org/W2021997546","https://openalex.org/W2022631295","https://openalex.org/W2045749719","https://openalex.org/W2051968191","https://openalex.org/W2054903578","https://openalex.org/W2065579444","https://openalex.org/W2070724313","https://openalex.org/W2082590892","https://openalex.org/W2084591647","https://openalex.org/W2086099702","https://openalex.org/W2088619985","https://openalex.org/W2090424610","https://openalex.org/W2096099694","https://openalex.org/W2097073572","https://openalex.org/W2100109944","https://openalex.org/W2101568317","https://openalex.org/W2106277226","https://openalex.org/W2109149397","https://openalex.org/W2136251662","https://openalex.org/W2136944379","https://openalex.org/W2157343005","https://openalex.org/W2170608472","https://openalex.org/W2194775991","https://openalex.org/W2316226477","https://openalex.org/W2369086172","https://openalex.org/W2476548250","https://openalex.org/W2511401065","https://openalex.org/W2512266304","https://openalex.org/W2520302833","https://openalex.org/W2520430674","https://openalex.org/W2533971697","https://openalex.org/W2593414223","https://openalex.org/W2604824122","https://openalex.org/W2752782242","https://openalex.org/W2753685993","https://openalex.org/W2761385227","https://openalex.org/W2766101120","https://openalex.org/W2766419681","https://openalex.org/W2768203249","https://openalex.org/W2770113520","https://openalex.org/W2776639132","https://openalex.org/W2785678896","https://openalex.org/W2792111852","https://openalex.org/W2797755516","https://openalex.org/W2848020186","https://openalex.org/W2891925951","https://openalex.org/W2892288283","https://openalex.org/W2893739000","https://openalex.org/W2895667927","https://openalex.org/W2901677542","https://openalex.org/W2952323569","https://openalex.org/W2954497554","https://openalex.org/W2963073614","https://openalex.org/W2963446712","https://openalex.org/W2963505747","https://openalex.org/W2964984565","https://openalex.org/W2982795046","https://openalex.org/W2983736948","https://openalex.org/W2993192098","https://openalex.org/W3016831894","https://openalex.org/W3016836866","https://openalex.org/W3034430110","https://openalex.org/W3035556176","https://openalex.org/W3035598238","https://openalex.org/W3099189289","https://openalex.org/W3100394409","https://openalex.org/W3117913765","https://openalex.org/W4299902414","https://openalex.org/W6629229403","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6735913928","https://openalex.org/W6736270120","https://openalex.org/W6741832134","https://openalex.org/W6765779288","https://openalex.org/W6775740815","https://openalex.org/W6776027025"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440","https://openalex.org/W2343470940"],"abstract_inverted_index":{"Hyperspectral":[0],"(HS)":[1],"reconstruction":[2,32,44,72,137],"from":[3,33,58,80,139],"RGB":[4,34,63,145],"images":[5,57,64,146],"denotes":[6],"the":[7,28,70,135],"recovery":[8],"of":[9],"whole-scene":[10],"HS":[11,31,43,56,71,136,150],"information,":[12],"which":[13],"has":[14],"attracted":[15],"much":[16],"attention":[17,123],"recently.":[18],"State-of-the-art":[19],"approaches":[20],"often":[21,38],"adopt":[22],"convolutional":[23],"neural":[24],"networks":[25],"to":[26,114,126,160,166],"learn":[27,127],"mapping":[29],"for":[30],"images.":[35],"However,":[36],"they":[37],"do":[39],"not":[40,66],"achieve":[41],"high":[42],"performance":[45,53,159],"across":[46,76],"different":[47,77,81],"scenes":[48,78],"consistently.":[49],"In":[50],"addition,":[51],"their":[52],"in":[54],"recovering":[55],"clean":[59,141],"and":[60,74,79,105,130,142],"real-world":[61,115,143],"noisy":[62,116,144],"is":[65,98],"consistent.":[67],"To":[68,111],"improve":[69],"accuracy":[73],"robustness":[75],"input":[82],"images,":[83,117],"we":[84,118],"present":[85],"an":[86],"effective":[87],"HSGAN":[88,156],"framework":[89],"with":[90],"a":[91,99,121],"two-stage":[92],"adversarial":[93],"training":[94],"strategy.":[95],"The":[96,152],"generator":[97],"four-level":[100],"top-down":[101],"architecture":[102],"that":[103,155],"extracts":[104],"combines":[106],"features":[107],"on":[108,147],"multiple":[109],"scales.":[110],"generalize":[112],"well":[113],"further":[119],"propose":[120],"spatial-spectral":[122],"block":[124],"(SSAB)":[125],"both":[128,140],"spatial-wise":[129],"channel-wise":[131],"relations.":[132],"We":[133],"conduct":[134],"experiments":[138],"five":[148],"well-known":[149],"datasets.":[151],"results":[153],"demonstrate":[154],"achieves":[157],"superior":[158],"existing":[161],"methods.":[162],"Please":[163],"visit":[164],"https://github.com/zhaoyuzhi/HSGAN":[165],"try":[167],"our":[168],"codes.":[169]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}