{"id":"https://openalex.org/W4417051817","doi":"https://doi.org/10.1109/tip.2025.3638151","title":"URDM: Hyperspectral Unmixing Regularized by Diffusion Models","display_name":"URDM: Hyperspectral Unmixing Regularized by Diffusion Models","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4417051817","doi":"https://doi.org/10.1109/tip.2025.3638151","pmid":"https://pubmed.ncbi.nlm.nih.gov/41348789"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2025.3638151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2025.3638151","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","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/A5100769200","display_name":"Min Zhao","orcid":"https://orcid.org/0000-0003-3258-8358"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Min Zhao","raw_affiliation_strings":["Department of Geography, The University of Hong Kong, Hong Kong, SAR, China"],"raw_orcid":"https://orcid.org/0000-0003-3258-8358","affiliations":[{"raw_affiliation_string":"Department of Geography, The University of Hong Kong, Hong Kong, SAR, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037873266","display_name":"Linruize Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linruize Tang","raw_affiliation_strings":["School of Artificial Intelligence and the School of Marine Science and Technology, Northwestern Polytechnical University, Xi&#x2019;an, China","School of Artificial Intelligence, School of Marine Science and Technology, Northwestern Polytechnical University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0009-0007-0253-729X","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and the School of Marine Science and Technology, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Artificial Intelligence, School of Marine Science and Technology, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333004","display_name":"Jie Chen","orcid":"https://orcid.org/0000-0003-2306-8860"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Chen","raw_affiliation_strings":["School of Artificial Intelligence and the School of Marine Science and Technology, Northwestern Polytechnical University, Xi&#x2019;an, China","School of Artificial Intelligence, School of Marine Science and Technology, Northwestern Polytechnical University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0003-2306-8860","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and the School of Marine Science and Technology, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Artificial Intelligence, School of Marine Science and Technology, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100705731","display_name":"Bo Huang","orcid":"https://orcid.org/0000-0002-5063-3522"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Bo Huang","raw_affiliation_strings":["Department of Geography, The University of Hong Kong, Hong Kong, SAR, China"],"raw_orcid":"https://orcid.org/0000-0002-5063-3522","affiliations":[{"raw_affiliation_string":"Department of Geography, The University of Hong Kong, Hong Kong, SAR, China","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45642866,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":null,"first_page":"8072","last_page":"8085"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9850000143051147,"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":0.9850000143051147,"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":0.0026000000070780516,"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":0.002199999988079071,"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":0.8680999875068665},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5295000076293945},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5055000185966492},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4625000059604645},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.42500001192092896},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.40380001068115234},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.3896999955177307},{"id":"https://openalex.org/keywords/diffusion-map","display_name":"Diffusion map","score":0.3855000138282776},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.38429999351501465},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.36559998989105225}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8680999875068665},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6047000288963318},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5889999866485596},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5295000076293945},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5055000185966492},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.42500001192092896},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.40380001068115234},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.3896999955177307},{"id":"https://openalex.org/C55128770","wikidata":"https://www.wikidata.org/wiki/Q5275440","display_name":"Diffusion map","level":4,"score":0.3855000138282776},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.38429999351501465},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.36559998989105225},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.362199991941452},{"id":"https://openalex.org/C6180225","wikidata":"https://www.wikidata.org/wiki/Q3411771","display_name":"Penalty method","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.3093999922275543},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3075999915599823},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.29789999127388},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.29739999771118164},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28790000081062317},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2637999951839447},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.26269999146461487},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.25519999861717224}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2025.3638151","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2025.3638151","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:41348789","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41348789","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7549897355","display_name":null,"funder_award_id":"2022YFB3903700","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7933956671","display_name":null,"funder_award_id":"42271439","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1873031189","https://openalex.org/W1964570608","https://openalex.org/W2015415108","https://openalex.org/W2063790512","https://openalex.org/W2069231830","https://openalex.org/W2095343758","https://openalex.org/W2119449590","https://openalex.org/W2131697388","https://openalex.org/W2157321686","https://openalex.org/W2163886442","https://openalex.org/W2508457857","https://openalex.org/W2587548727","https://openalex.org/W2770508708","https://openalex.org/W2773194520","https://openalex.org/W2886666371","https://openalex.org/W2910655660","https://openalex.org/W3012359476","https://openalex.org/W3028000844","https://openalex.org/W3097505512","https://openalex.org/W3112538150","https://openalex.org/W3137191419","https://openalex.org/W3151666947","https://openalex.org/W3154556605","https://openalex.org/W3166330239","https://openalex.org/W3204957802","https://openalex.org/W4206259850","https://openalex.org/W4211249244","https://openalex.org/W4226336696","https://openalex.org/W4285199914","https://openalex.org/W4289656123","https://openalex.org/W4297397016","https://openalex.org/W4316661198","https://openalex.org/W4319663720","https://openalex.org/W4322490806","https://openalex.org/W4324116601","https://openalex.org/W4383220030","https://openalex.org/W4385804996","https://openalex.org/W4386649074","https://openalex.org/W4387385639","https://openalex.org/W4387587535","https://openalex.org/W4390691874","https://openalex.org/W4390872797","https://openalex.org/W4392909637","https://openalex.org/W4394744634","https://openalex.org/W4399310742","https://openalex.org/W4400448283","https://openalex.org/W4402716156","https://openalex.org/W4402754016","https://openalex.org/W4414197963"],"related_works":[],"abstract_inverted_index":{"Hyperspectral":[0],"unmixing":[1,28,37,66,91,121],"aims":[2],"to":[3,33,99,136,154,161],"decompose":[4],"the":[5,36,57,61,106,120,148,178],"mixed":[6],"pixels":[7],"into":[8,131,164],"pure":[9],"spectra":[10],"and":[11,80,113,128,174,180],"calculate":[12],"their":[13,43],"corresponding":[14],"fractional":[15],"abundances.":[16],"It":[17],"holds":[18],"a":[19,88,95,125,132,141,158],"critical":[20],"position":[21],"in":[22],"hyperspectral":[23,90],"image":[24],"processing.":[25],"Traditional":[26],"model-based":[27],"methods":[29,67],"use":[30],"convex":[31],"optimization":[32,111],"iteratively":[34],"solve":[35],"problem":[38],"with":[39],"hand-crafted":[40],"regularizers.":[41],"While":[42],"performance":[44,182],"is":[45,152],"limited":[46,78],"by":[47,94],"these":[48,101],"manually":[49],"designed":[50],"constraints,":[51],"which":[52],"may":[53],"not":[54],"fully":[55],"capture":[56],"structural":[58],"information":[59],"of":[60,108,183],"data.":[62],"Recently,":[63],"deep":[64,114],"learning-based":[65],"have":[68,77],"shown":[69],"remarkable":[70],"capability":[71],"for":[72],"this":[73,84],"task.":[74],"However,":[75],"they":[76],"generalizability":[79],"lack":[81],"interpretability.":[82],"In":[83],"paper,":[85],"we":[86,118,156],"propose":[87],"novel":[89],"method":[92,104],"regularized":[93],"diffusion":[96,133,143],"model":[97,145],"(URDM)":[98],"overcome":[100],"shortcomings.":[102],"Our":[103],"leverages":[105],"advantages":[107],"both":[109,172],"conventional":[110],"algorithms":[112],"generative":[115,138],"models.":[116],"Specifically,":[117],"formulate":[119],"objective":[122,150],"function":[123,151],"from":[124,140],"variational":[126],"perspective":[127],"integrate":[129],"it":[130,163],"sampling":[134],"process":[135],"introduce":[137,157],"priors":[139],"denoising":[142],"probabilistic":[144],"(DDPM).":[146],"Since":[147],"original":[149],"challenging":[153],"optimize,":[155],"splitting-based":[159],"strategy":[160],"decouple":[162],"simpler":[165],"subproblems.":[166],"Extensive":[167],"experiment":[168],"results":[169],"conducted":[170],"on":[171],"synthetic":[173],"real":[175],"datasets":[176],"demonstrate":[177],"efficiency":[179],"superior":[181],"our":[184],"proposed":[185],"method.":[186]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-12-05T00:00:00"}
