{"id":"https://openalex.org/W3207713882","doi":"https://doi.org/10.1109/igarss47720.2021.9553257","title":"Learning a Model-Based Deep Hyperspectral Denoiser from a Single Noisy Hyperspectral Image","display_name":"Learning a Model-Based Deep Hyperspectral Denoiser from a Single Noisy Hyperspectral Image","publication_year":2021,"publication_date":"2021-07-11","ids":{"openalex":"https://openalex.org/W3207713882","doi":"https://doi.org/10.1109/igarss47720.2021.9553257","mag":"3207713882"},"language":"en","primary_location":{"id":"doi:10.1109/igarss47720.2021.9553257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553257","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"},"type":"conference-paper","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/A5062218391","display_name":"Guanyiman Fu","orcid":"https://orcid.org/0000-0002-2256-5876"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanyiman Fu","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033291716","display_name":"Fengchao Xiong","orcid":"https://orcid.org/0000-0002-9753-4919"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengchao Xiong","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088585137","display_name":"Shuyin Tao","orcid":"https://orcid.org/0000-0002-3569-8141"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuyin Tao","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037595310","display_name":"Jianfeng Lu","orcid":"https://orcid.org/0000-0002-9190-507X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Lu","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100781212","display_name":"Jun Zhou","orcid":"https://orcid.org/0000-0001-5822-8233"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["School of Information and Communication Technology, Griffith University, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Technology, Griffith University, Australia","institution_ids":["https://openalex.org/I11701301"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059857918","display_name":"Yuntao Qian","orcid":"https://orcid.org/0000-0002-7418-5891"},"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":"Yuntao Qian","raw_affiliation_strings":["College of Computer Science, Zhejiang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998999834060669,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998999834060669,"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":0.9995999932289124,"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":0.9993000030517578,"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":0.7949305772781372},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6919243931770325},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6871166229248047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6372294425964355},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5638088583946228},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.45142310857772827},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.411997526884079}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7949305772781372},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6919243931770325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6871166229248047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6372294425964355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5638088583946228},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.45142310857772827},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.411997526884079}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss47720.2021.9553257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss47720.2021.9553257","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS","raw_type":"proceedings-article"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/414075","is_oa":false,"landing_page_url":"http://hdl.handle.net/10072/414075","pdf_url":null,"source":{"id":"https://openalex.org/S4306402548","display_name":"Griffith Research Online (Griffith University, Queensland, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11701301","host_organization_name":"Griffith University","host_organization_lineage":["https://openalex.org/I11701301"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference output"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5400000214576721,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1985242206","https://openalex.org/W2030927653","https://openalex.org/W2056370875","https://openalex.org/W2095906131","https://openalex.org/W2508457857","https://openalex.org/W2953231542","https://openalex.org/W2986132184","https://openalex.org/W2991209609","https://openalex.org/W3098337560","https://openalex.org/W6658145091","https://openalex.org/W6664401941","https://openalex.org/W6725080326"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W2027399350","https://openalex.org/W2060875994","https://openalex.org/W2044184146","https://openalex.org/W2019190440","https://openalex.org/W3034864990","https://openalex.org/W1766550789"],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1,56],"(HSI)":[2],"denoising":[3,31,71,84,101],"is":[4,156],"a":[5,34,78,99,123,149,159,180],"crucial":[6],"preprocessing":[7],"procedure":[8],"to":[9,85,121,134],"improve":[10],"the":[11,18,22,49,87,110,114,136,190],"quality":[12],"of":[13,24,37,52,67,89,116,138,161,182,192],"HSI.":[14,151],"Model-based":[15],"methods":[16,46,91],"take":[17],"degradation":[19],"model":[20,102],"and":[21,40,54,92,174,198],"structure":[23],"underlying":[25],"clean":[26,53],"HSI":[27,57,83,100,140,155],"into":[28,158],"account":[29],"for":[30,82,130,142,185],"but":[32,59],"require":[33],"large":[35],"number":[36,160],"numerical":[38],"iterations":[39],"exhausting":[41],"parameter":[42],"tuning.":[43],"Deep-learning-based":[44],"(DL-based)":[45],"directly":[47,145],"learn":[48,146],"nonlinear":[50],"transformation":[51],"noisy":[55,154],"pairs,":[58],"rely":[60],"on":[61,104,195],"large-scale":[62],"high-quality":[63],"training":[64],"samples":[65],"because":[66],"its":[68],"\u201cblack":[69],"box\u201d":[70],"mechanism.":[72],"In":[73,132],"this":[74],"paper,":[75],"we":[76,96,108,144],"propose":[77],"model-based":[79,90],"DL":[80],"method":[81,194],"combine":[86],"advantages":[88],"DL-based":[93],"methods.":[94],"Specifically,":[95],"first":[97],"build":[98],"based":[103],"sparse":[105],"representation.":[106],"Then,":[107],"unfold":[109],"iterative":[111],"optimization":[112],"under":[113],"framework":[115],"gradient":[117],"descent":[118],"with":[119],"momentum":[120],"yield":[122],"Gradient":[124],"Momentum":[125],"Sparse":[126],"Coding":[127],"Network":[128],"(GMSC-Net)":[129],"denoising.":[131],"order":[133],"overcome":[135],"unavailability":[137],"noisy-clean":[139],"pairs":[141,184],"training,":[143],"GMSC-Net":[147],"from":[148],"single":[150],"The":[152,166],"observed":[153],"grouped":[157],"clusters":[162],"containing":[163],"local":[164],"cubes.":[165],"cluster":[167],"centers":[168],"are":[169,175],"treated":[170],"as":[171],"\u201cclean\u201d":[172],"cubes":[173],"polluted":[176],"by":[177],"noises,":[178],"yielding":[179],"set":[181],"\u201cnoisy-clean\u201d":[183],"training.":[186],"Extensive":[187],"experiments":[188],"show":[189],"effectiveness":[191],"our":[193],"both":[196],"synthetic":[197],"real-world":[199],"datasets.":[200]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
