{"id":"https://openalex.org/W4387803699","doi":"https://doi.org/10.1109/igarss52108.2023.10282110","title":"Poissonian Hyperspectral Image Denoising without Using Anscombe Transform","display_name":"Poissonian Hyperspectral Image Denoising without Using Anscombe Transform","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387803699","doi":"https://doi.org/10.1109/igarss52108.2023.10282110"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10282110","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-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":"https://openalex.org/A5100661961","display_name":"Yulan Wang","orcid":"https://orcid.org/0000-0002-5600-5455"},"institutions":[{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"funder","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210114963","display_name":"Chinese Academy of Surveying and Mapping","ror":"https://ror.org/02j693n47","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114963"]},{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yulan Wang","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics,College of Electronic and Information Engineering,Nanjing,China,210016","Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing Institute of Surveying and Mapping, Beijing, China","Key Laboratory of Land Satellite Remote Sensing Application, Ministry of Natural Resources, Jiangsu Province Surveying and Mapping Engineering Institute, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics,College of Electronic and Information Engineering,Nanjing,China,210016","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing Institute of Surveying and Mapping, Beijing, China","institution_ids":["https://openalex.org/I4210114963"]},{"raw_affiliation_string":"Key Laboratory of Land Satellite Remote Sensing Application, Ministry of Natural Resources, Jiangsu Province Surveying and Mapping Engineering Institute, Nanjing, China","institution_ids":["https://openalex.org/I211433327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396024","display_name":"Peng Wang","orcid":"https://orcid.org/0000-0002-3825-6365"},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]},{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Wang","raw_affiliation_strings":["Chang'an University,Xi’an Key Laboratory of Territorial Spatial Information,Xi’an,China,710064","Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Chang'an University,Xi’an Key Laboratory of Territorial Spatial Information,Xi’an,China,710064","institution_ids":["https://openalex.org/I25355098"]},{"raw_affiliation_string":"Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102949838","display_name":"Xiwang Zhang","orcid":"https://orcid.org/0000-0002-9651-596X"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiwang Zhang","raw_affiliation_strings":["Henan University,Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education,Kaifeng,China,475001"],"affiliations":[{"raw_affiliation_string":"Henan University,Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education,Kaifeng,China,475001","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440604","display_name":"Jue Wang","orcid":"https://orcid.org/0000-0002-3641-3136"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]},{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]},{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jue Wang","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics,College of Electronic and Information Engineering,Nanjing,China,210016","Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, China","Rady School of Management, University of California, San Diego, California, USA"],"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics,College of Electronic and Information Engineering,Nanjing,China,210016","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng, China","institution_ids":["https://openalex.org/I173899330"]},{"raw_affiliation_string":"Rady School of Management, University of California, San Diego, California, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011308573","display_name":"Matthieu Muller","orcid":"https://orcid.org/0009-0008-5631-7601"},"institutions":[{"id":"https://openalex.org/I4210124956","display_name":"Grenoble Images Parole Signal Automatique","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Matthieu Muller","raw_affiliation_strings":["University Grenoble Alpes,CNRS, Grenoble INP, GIPSA-lab,Grenoble,France,38000"],"affiliations":[{"raw_affiliation_string":"University Grenoble Alpes,CNRS, Grenoble INP, GIPSA-lab,Grenoble,France,38000","institution_ids":["https://openalex.org/I4210124956","https://openalex.org/I1294671590","https://openalex.org/I899635006","https://openalex.org/I106785703"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100661961"],"corresponding_institution_ids":["https://openalex.org/I211433327","https://openalex.org/I4210114963","https://openalex.org/I9842412"],"apc_list":null,"apc_paid":null,"fwci":0.123,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.42673277,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"10","issue":null,"first_page":"7300","last_page":"7303"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":1.0,"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":1.0,"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/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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9961000084877014,"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":0.8006656765937805},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.7565511465072632},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6276944875717163},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5996149778366089},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5962575078010559},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.5738113522529602},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5387372374534607},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.5177530646324158},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.516160786151886},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.508525013923645},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5079191327095032},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.48962122201919556},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4560844600200653},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44601112604141235},{"id":"https://openalex.org/keywords/non-local-means","display_name":"Non-local means","score":0.4236987829208374},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3662468194961548},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3511141836643219},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23262599110603333},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.1422261893749237},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.06686830520629883},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06378772854804993}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8006656765937805},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.7565511465072632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6276944875717163},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5996149778366089},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5962575078010559},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.5738113522529602},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5387372374534607},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.5177530646324158},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.516160786151886},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.508525013923645},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5079191327095032},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.48962122201919556},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4560844600200653},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44601112604141235},{"id":"https://openalex.org/C101453961","wikidata":"https://www.wikidata.org/wiki/Q7048948","display_name":"Non-local means","level":4,"score":0.4236987829208374},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3662468194961548},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3511141836643219},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23262599110603333},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.1422261893749237},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.06686830520629883},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06378772854804993},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss52108.2023.10282110","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310282","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02ntv3742"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322878","display_name":"Henan University","ror":"https://ror.org/003xyzq10"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1190918437","https://openalex.org/W1978333359","https://openalex.org/W1982956952","https://openalex.org/W1987057208","https://openalex.org/W2021262032","https://openalex.org/W2114341361","https://openalex.org/W2140702875","https://openalex.org/W2142192675","https://openalex.org/W2773415061","https://openalex.org/W2790888198","https://openalex.org/W2964179170","https://openalex.org/W3040323135","https://openalex.org/W3101833857","https://openalex.org/W3201553497","https://openalex.org/W4323064998","https://openalex.org/W4323644249","https://openalex.org/W6627944744"],"related_works":["https://openalex.org/W2098237619","https://openalex.org/W2080558231","https://openalex.org/W2123496732","https://openalex.org/W2097073572","https://openalex.org/W3046917719","https://openalex.org/W1032107053","https://openalex.org/W1538114257","https://openalex.org/W2080991836","https://openalex.org/W1982832860","https://openalex.org/W2035842925"],"abstract_inverted_index":{"In":[0,39],"the":[1,31,58,64,72,76,83,92],"most":[2,100],"existing":[3],"Hyperspectral":[4],"Image":[5],"(HSI)":[6],"denoising":[7,33,48,102],"methods,":[8],"Poisson":[9,79],"noise":[10,16,59],"is":[11],"first":[12],"transformed":[13],"into":[14],"Gaussian":[15],"through":[17],"Anscombe":[18,37,52],"transform":[19,25,53],"and":[20],"then":[21],"remove":[22,57],"it.":[23],"However,":[24],"errors":[26],"may":[27],"occur":[28],"that":[29,91],"affect":[30],"final":[32],"results":[34,89],"when":[35],"using":[36,51],"transform.":[38],"this":[40],"paper,":[41],"we":[42],"propose":[43],"a":[44,66],"Poissonian":[45,61],"hyperspectral":[46],"image":[47],"method":[49,94],"without":[50],"(WUAT)":[54],"to":[55],"directly":[56],"of":[60,75],"HSI":[62],"under":[63],"maximum":[65],"posteriori":[67],"(MAP)":[68],"model":[69],"by":[70],"finding":[71],"minimum":[73],"value":[74],"negative":[77],"logarithmic":[78],"log-likelihood":[80],"combined":[81],"with":[82],"total":[84],"variation":[85],"(TV).":[86],"The":[87],"experimental":[88],"show":[90],"proposed":[93],"can":[95],"acquire":[96],"better":[97],"performance":[98],"than":[99],"state-of-the-art":[101],"methods.":[103]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}