{"id":"https://openalex.org/W4320917930","doi":"https://doi.org/10.3390/rs15041058","title":"Robust Hyperspectral Unmixing with Practical Learning-Based Hyperspectral Image Denoising","display_name":"Robust Hyperspectral Unmixing with Practical Learning-Based Hyperspectral Image Denoising","publication_year":2023,"publication_date":"2023-02-15","ids":{"openalex":"https://openalex.org/W4320917930","doi":"https://doi.org/10.3390/rs15041058"},"language":"en","primary_location":{"id":"doi:10.3390/rs15041058","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15041058","pdf_url":"https://www.mdpi.com/2072-4292/15/4/1058/pdf?version=1676453972","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/4/1058/pdf?version=1676453972","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033632828","display_name":"Risheng Huang","orcid":"https://orcid.org/0000-0001-6661-023X"},"institutions":[{"id":"https://openalex.org/I192209268","display_name":"Shaoxing University","ror":"https://ror.org/0435tej63","country_code":"CN","type":"education","lineage":["https://openalex.org/I192209268"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Risheng Huang","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, Shaoxing University, Shaoxing 312000, China"],"raw_orcid":"https://orcid.org/0000-0001-6661-023X","affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, Shaoxing University, Shaoxing 312000, China","institution_ids":["https://openalex.org/I192209268"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062771797","display_name":"Xiaorun Li","orcid":"https://orcid.org/0000-0002-4312-7533"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaorun Li","raw_affiliation_strings":["College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059781919","display_name":"Yiming Fang","orcid":"https://orcid.org/0000-0002-4798-8189"},"institutions":[{"id":"https://openalex.org/I192209268","display_name":"Shaoxing University","ror":"https://ror.org/0435tej63","country_code":"CN","type":"education","lineage":["https://openalex.org/I192209268"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiming Fang","raw_affiliation_strings":["School of Mechanical and Electrical Engineering, Shaoxing University, Shaoxing 312000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Electrical Engineering, Shaoxing University, Shaoxing 312000, China","institution_ids":["https://openalex.org/I192209268"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118899994","display_name":"Zeyu Cao","orcid":"https://orcid.org/0000-0002-1566-2408"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zeyu Cao","raw_affiliation_strings":["College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017674477","display_name":"Chaoqun Xia","orcid":"https://orcid.org/0000-0002-0167-0423"},"institutions":[{"id":"https://openalex.org/I146620803","display_name":"Wenzhou University","ror":"https://ror.org/020hxh324","country_code":"CN","type":"education","lineage":["https://openalex.org/I146620803"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoqun Xia","raw_affiliation_strings":["College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, China","institution_ids":["https://openalex.org/I146620803"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5118899994"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2784},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2784},"fwci":0.5394,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.6351688,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"15","issue":"4","first_page":"1058","last_page":"1058"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9994000196456909,"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":0.9980999827384949,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9299777746200562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.735133171081543},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6633706092834473},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6611864566802979},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6392189264297485},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5198131799697876},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3596775233745575},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3321439027786255}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9299777746200562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.735133171081543},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6633706092834473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6611864566802979},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6392189264297485},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5198131799697876},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3596775233745575},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3321439027786255}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15041058","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15041058","pdf_url":"https://www.mdpi.com/2072-4292/15/4/1058/pdf?version=1676453972","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fdd80707b926491ca18d157d0059a726","is_oa":true,"landing_page_url":"https://doaj.org/article/fdd80707b926491ca18d157d0059a726","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,"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":"Remote Sensing, Vol 15, Iss 4, p 1058 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/4/1058/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15041058","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15041058","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15041058","pdf_url":"https://www.mdpi.com/2072-4292/15/4/1058/pdf?version=1676453972","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4320917930.pdf"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1531818640","https://openalex.org/W1537281681","https://openalex.org/W1974438823","https://openalex.org/W1996452481","https://openalex.org/W2002469984","https://openalex.org/W2032944446","https://openalex.org/W2062403535","https://openalex.org/W2063069198","https://openalex.org/W2126926806","https://openalex.org/W2142192675","https://openalex.org/W2163886442","https://openalex.org/W2169466597","https://openalex.org/W2171837816","https://openalex.org/W2328456116","https://openalex.org/W2334023959","https://openalex.org/W2344025572","https://openalex.org/W2467741384","https://openalex.org/W2490201121","https://openalex.org/W2520430674","https://openalex.org/W2566928557","https://openalex.org/W2766940489","https://openalex.org/W2782517596","https://openalex.org/W2790528326","https://openalex.org/W2806155925","https://openalex.org/W2920302576","https://openalex.org/W2950566305","https://openalex.org/W2955863859","https://openalex.org/W2963213461","https://openalex.org/W2966113161","https://openalex.org/W2985303383","https://openalex.org/W3013064625","https://openalex.org/W3036007026","https://openalex.org/W3098435832","https://openalex.org/W3110194847","https://openalex.org/W3119609454","https://openalex.org/W4214543554","https://openalex.org/W4281395053","https://openalex.org/W4295409451"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W2060875994","https://openalex.org/W2027399350","https://openalex.org/W2044184146","https://openalex.org/W3034789145","https://openalex.org/W4367628250","https://openalex.org/W383418545"],"abstract_inverted_index":{"The":[0,19,113,172],"noise":[1,20,48,79,91,99],"corruption":[2],"problem":[3],"commonly":[4],"exists":[5],"in":[6,23,31,151],"hyperspectral":[7,16,66,72,82,115],"images":[8],"(HSIs)":[9],"and":[10,28,36,84,105,125,178,193],"severely":[11],"affects":[12],"the":[13,58,90,94,97,121,131,147,155,166,169,197],"accuracy":[14,148],"of":[15,96,136,149,168],"unmixing":[17,51,59,67,132,137,150,160,198],"algorithms.":[18],"formulation":[21],"existing":[22],"HSIs":[24],"is":[25],"relatively":[26],"complex":[27],"would":[29],"change":[30],"conjunction":[32],"with":[33,69,189],"different":[34],"devices":[35],"imaging":[37],"settings.":[38],"For":[39],"real":[40,179],"applications,":[41],"applying":[42],"denoising":[43,111,123],"approaches":[44],"without":[45],"accurate":[46],"close-to-reality":[47,78],"modeling":[49],"before":[50],"may":[52],"not":[53],"improve,":[54],"but":[55],"rather":[56],"degrade":[57],"performance.":[60],"This":[61],"study":[62],"proposes":[63],"a":[64,77,86,109],"robust":[65],"method":[68,144,184],"practical":[70],"learning-based":[71],"image":[73],"denoising.":[74],"We":[75],"formulated":[76],"model":[80],"for":[81,89,107],"data":[83,102,116,188],"provide":[85],"calibration":[87],"approach":[88],"parameters.":[92],"On":[93],"basis":[95],"calibrated":[98],"model,":[100],"synthetic":[101,177],"were":[103,117,126,162],"generated":[104],"used":[106,128,159],"training":[108],"KST-based":[110],"network.":[112],"noisy":[114,152],"firstly":[118],"denoised":[119],"by":[120],"trained":[122],"network":[124],"then":[127],"to":[129,145,164,195],"perform":[130],"process.":[133],"A":[134],"variety":[135],"algorithms":[138,161],"can":[139,185],"be":[140],"integrated":[141],"into":[142],"our":[143,182],"improve":[146,196],"situations.":[153],"In":[154],"experiments,":[156],"several":[157],"widely":[158],"employed":[163],"verify":[165],"effect":[167],"proposed":[170,183],"method.":[171],"experimental":[173],"results":[174],"on":[175],"both":[176],"demonstrated":[180],"that":[181],"handle":[186],"HSI":[187],"various":[190],"gain":[191],"settings":[192],"helps":[194],"performance":[199],"effectively.":[200]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}