{"id":"https://openalex.org/W7093351134","doi":"https://doi.org/10.1109/lgrs.2025.3624612","title":"Multiscale Spatial\u2013Spectral Attention Network for Hyperspectral Image Compressed Sensing","display_name":"Multiscale Spatial\u2013Spectral Attention Network for Hyperspectral Image Compressed Sensing","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7093351134","doi":"https://doi.org/10.1109/lgrs.2025.3624612"},"language":null,"primary_location":{"id":"doi:10.1109/lgrs.2025.3624612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3624612","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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":null,"display_name":"Shen Dong","orcid":"https://orcid.org/0009-0003-4983-2115"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shen Dong","raw_affiliation_strings":["School of Cyber Science and Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jing Xiao","orcid":"https://orcid.org/0000-0002-0833-5679"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Xiao","raw_affiliation_strings":["School of Artificial Intelligence, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhen Zhang","orcid":"https://orcid.org/0009-0001-9124-2309"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Huawei Li","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huawei Li","raw_affiliation_strings":["School of Artificial Intelligence, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":null,"display_name":"Liang Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Liao","raw_affiliation_strings":["Hangzhou Institute of Technology, Xidian University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Institute of Technology, Xidian University, Hangzhou, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.60589319,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.44850000739097595,"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":0.44850000739097595,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.2363000065088272,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.07599999755620956,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8011000156402588},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6424999833106995},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6412000060081482},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.567799985408783},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.534500002861023},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5245000123977661},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5095999836921692},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4941999912261963},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.3580999970436096}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8011000156402588},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7766000032424927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6669999957084656},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6424999833106995},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6412000060081482},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.567799985408783},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.534500002861023},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5245000123977661},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5095999836921692},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4941999912261963},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40869998931884766},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.35179999470710754},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3490000069141388},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.328000009059906},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.31929999589920044},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.29980000853538513},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.2915000021457672},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28279998898506165},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.28060001134872437},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C7545210","wikidata":"https://www.wikidata.org/wiki/Q838123","display_name":"Data redundancy","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C39399123","wikidata":"https://www.wikidata.org/wiki/Q1348989","display_name":"Earth observation","level":3,"score":0.267300009727478},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.25940001010894775},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3624612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3624612","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3114819178","display_name":null,"funder_award_id":"2023QNRC001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3591741923","display_name":null,"funder_award_id":"62371351","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5055832376","display_name":null,"funder_award_id":"ZYTS25036","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7167553242","display_name":null,"funder_award_id":"62571397","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8093789298","display_name":null,"funder_award_id":"62202349","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W609694675","https://openalex.org/W1996699294","https://openalex.org/W2018851907","https://openalex.org/W2039240409","https://openalex.org/W2040903332","https://openalex.org/W2114770744","https://openalex.org/W2752782242","https://openalex.org/W2768095459","https://openalex.org/W3042671644","https://openalex.org/W3102507295","https://openalex.org/W3124791240","https://openalex.org/W4220688292","https://openalex.org/W4289752563","https://openalex.org/W4386766984","https://openalex.org/W4389352462","https://openalex.org/W4392909584","https://openalex.org/W4398162674","https://openalex.org/W4402916130"],"related_works":[],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1,66],"(HSI)":[2],"compressed":[3,82],"sensing":[4,83],"faces":[5],"challenges":[6],"due":[7,49],"to":[8,50,114,193],"spectral":[9,40,126],"redundancy":[10],"and":[11,91,124,185],"high":[12],"dimensionality.":[13],"Although":[14],"recent":[15],"learning-based":[16],"methods":[17,60],"have":[18],"shown":[19],"promise,":[20],"most":[21],"of":[22,46,53,84,152,168],"them":[23],"rely":[24],"heavily":[25],"on":[26,145],"spatial":[27,130,138],"convolutional":[28,99],"operations,":[29],"which":[30],"are":[31],"often":[32],"insufficient":[33],"in":[34,176,182,189],"capturing":[35],"the":[36,44,51,129,150],"complex":[37,117],"dependencies":[38,119],"among":[39],"bands,":[41],"thereby":[42],"limiting":[43],"quality":[45],"reconstruction.":[47],"Moreover,":[48],"use":[52],"stripe-like":[54],"images":[55],"as":[56],"input-output":[57],"pairs,":[58],"these":[59,70],"inevitably":[61],"introduce":[62],"grid-like":[63,134],"artifacts":[64,135],"during":[65],"stitching.":[67],"To":[68],"address":[69],"challenges,":[71],"we":[72],"propose":[73],"a":[74,87,110,165,173,179,186],"novel":[75],"Multi-scale":[76,90],"Spatial-Spectral":[77],"Attention":[78],"Network":[79],"(SSANet)":[80],"for":[81,199],"HSIs,":[85],"featuring":[86],"newly":[88],"developed":[89],"Multi-attention":[92],"Fusion":[93],"(MMF)":[94],"module":[95,108],"that":[96],"interactively":[97],"combines":[98],"feature":[100],"extraction":[101],"with":[102,155],"dual-path":[103],"attention":[104,131],"mechanisms.":[105],"The":[106],"MMF":[107],"employs":[109],"hybrid":[111],"pooling":[112],"strategy":[113],"effectively":[115],"model":[116],"spatial-spectral":[118],"while":[120],"maintaining":[121],"computational":[122],"efficiency":[123],"preserving":[125],"details.":[127],"Additionally,":[128],"component":[132],"mitigates":[133],"by":[136],"enforcing":[137],"consistency":[139],"across":[140,159],"patch":[141],"boundaries.":[142],"Extensive":[143],"experiments":[144],"standard":[146],"HSI":[147,200],"benchmarks":[148],"demonstrate":[149],"superiority":[151],"our":[153],"approach":[154],"consistent":[156],"noise":[157],"robustness":[158],"varying":[160],"sampling":[161,166],"rates.":[162],"Specifically,":[163],"at":[164],"rate":[167],"just":[169],"1%,":[170],"SSANet":[171],"achieves":[172],"9.5%":[174],"reduction":[175,181],"SAM":[177],"(std=0.069),":[178],"40.7%":[180],"RMSE":[183],"(std=0.245),":[184],"4%":[187],"increase":[188],"PSNR":[190],"(std=0.195)":[191],"compared":[192],"state-of-the-art":[194],"methods,":[195],"validating":[196],"its":[197],"effectiveness":[198],"reconstruction":[201],"tasks.":[202]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-24T00:00:00"}
