{"id":"https://openalex.org/W7138432586","doi":"https://doi.org/10.1609/aaai.v40i6.42477","title":"NODiff: Neural Operator Diffusion for Multispectral Image Fusion","display_name":"NODiff: Neural Operator Diffusion for Multispectral Image Fusion","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138432586","doi":"https://doi.org/10.1609/aaai.v40i6.42477"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i6.42477","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i6.42477","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/42477/46438","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/42477/46438","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129747765","display_name":"Junming Hou","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Junming Hou","raw_affiliation_strings":["Southeast University"],"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129736564","display_name":"Ran Ran","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Ran","raw_affiliation_strings":["University of Electronic Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129741121","display_name":"Sixing Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sixing Chen","raw_affiliation_strings":["Southeast University"],"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100434161","display_name":"Zihao Chen","orcid":"https://orcid.org/0000-0001-7838-4989"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zihao Chen","raw_affiliation_strings":["Southeast University"],"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129735804","display_name":"Xiaofeng Cong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaofeng Cong","raw_affiliation_strings":["Southeast University"],"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129643445","display_name":"Junling Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junling Li","raw_affiliation_strings":["Southeast University"],"affiliations":[{"raw_affiliation_string":"Southeast University","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129730332","display_name":"Liang-Jian Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang-Jian Deng","raw_affiliation_strings":["University of Electronic Science and Technology of China\nMulti-Hazard Early Warning Key Laboratory of Sichuan Province"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China\nMulti-Hazard Early Warning Key Laboratory of Sichuan Province","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5129747765"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59677419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"6","first_page":"4753","last_page":"4761"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9879999756813049,"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":0.9879999756813049,"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":0.003599999938160181,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.002300000051036477,"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/multispectral-image","display_name":"Multispectral image","score":0.6662999987602234},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.43860000371932983},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.43380001187324524},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.42820000648498535},{"id":"https://openalex.org/keywords/panchromatic-film","display_name":"Panchromatic film","score":0.38760000467300415},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.36010000109672546},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.3589000105857849},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35510000586509705}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7817999720573425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6676999926567078},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.6662999987602234},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.43860000371932983},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.43380001187324524},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.42820000648498535},{"id":"https://openalex.org/C107445234","wikidata":"https://www.wikidata.org/wiki/Q280995","display_name":"Panchromatic film","level":3,"score":0.38760000467300415},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3855000138282776},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.36010000109672546},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.3589000105857849},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35510000586509705},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3547999858856201},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3147999942302704},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.3050999939441681},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2775999903678894},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.2540999948978424},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i6.42477","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i6.42477","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/42477/46438","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i6.42477","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i6.42477","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/42477/46438","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.4650435447692871,"id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G1541561893","display_name":null,"funder_award_id":"62301151","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3002070488","display_name":null,"funder_award_id":"2025YFNH0001","funder_id":"https://openalex.org/F4320322922","funder_display_name":"Department of Science and Technology of Sichuan Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322922","display_name":"Department of Science and Technology of Sichuan Province","ror":"https://ror.org/04323m874"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138432586.pdf","grobid_xml":"https://content.openalex.org/works/W7138432586.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Pansharpening":[0],"is":[1,155],"a":[2,68,80,105,135,151],"powerful":[3],"technique":[4],"for":[5,96,125,145],"generating":[6,146],"high-resolution":[7,121],"multispectral":[8,19],"(HRMS)":[9],"images":[10],"by":[11,164],"fusing":[12],"currently":[13],"available":[14],"image":[15],"pairs":[16],"of":[17,31],"low-resolution":[18],"(LRMS)":[20],"and":[21,51,87,133,185],"texture-rich":[22],"panchromatic":[23],"(PAN)":[24],"data,":[25],"effectively":[26],"addressing":[27],"the":[28,74,112,120,130],"physical":[29],"constraints":[30],"satellite":[32,60],"sensors.":[33],"While":[34],"recent":[35],"generative":[36,88,198],"diffusion":[37,70,116],"models":[38],"have":[39],"demonstrated":[40],"impressive":[41],"performance":[42,180],"gains":[43],"in":[44,56],"this":[45,63],"domain,":[46],"their":[47],"prohibitive":[48],"computational":[49],"demands":[50],"training":[52,184],"costs":[53],"hinder":[54],"practicality":[55],"resource-constrained":[57],"remote":[58],"sensing":[59],"systems.":[61],"In":[62,98],"work,":[64],"we":[65,100,110,128],"propose":[66],"NODiff,":[67],"novel":[69],"framework":[71],"that":[72,175],"replaces":[73],"conventional":[75],"attention-based":[76],"denoising":[77],"backbone":[78],"with":[79],"neural":[81],"operator,":[82],"seamlessly":[83],"integrating":[84],"operator":[85],"learning":[86,107],"modeling":[89],"into":[90,195],"an":[91],"efficient":[92,143],"yet":[93],"effective":[94],"solution":[95],"pansharpening.":[97,126],"practice,":[99],"implement":[101],"our":[102,190],"approach":[103],"through":[104],"two-stage":[106],"paradigm:":[108],"First,":[109],"pretrain":[111],"proposed":[113],"Neural":[114],"Operator-based":[115],"model":[117],"to":[118,141,157],"learn":[119],"texture":[122],"priors":[123],"essential":[124],"Afterward,":[127],"freeze":[129],"pretrained":[131],"parameters,":[132],"design":[134],"lightweight":[136],"conditional":[137],"detail":[138],"guidance":[139],"adapter":[140],"enable":[142],"fine-tuning":[144],"desired":[147],"HRMS":[148],"images.":[149],"Meanwhile,":[150],"time-aware":[152],"low-rank":[153],"adaptation":[154],"introduced":[156],"dynamically":[158],"refine":[159],"high-frequency":[160],"details":[161],"potentially":[162],"affected":[163],"spectral":[165],"mode":[166],"truncation.":[167],"Extensive":[168],"experiments":[169],"on":[170],"multiple":[171],"benchmark":[172],"datasets":[173],"demonstrate":[174],"NODiff":[176],"achieves":[177],"competitive":[178],"pansharpening":[179],"while":[181],"significantly":[182],"reducing":[183],"inference":[186],"costs.":[187],"Beyond":[188],"pansharpening,":[189],"method":[191],"provides":[192],"new":[193],"insights":[194],"building":[196],"resource-efficient":[197],"models.":[199]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2026-03-18T00:00:00"}
