{"id":"https://openalex.org/W4416873282","doi":"https://doi.org/10.1109/tgrs.2025.3638896","title":"DiffFuSR: Super-Resolution of All Sentinel-2 Multispectral Bands Using Diffusion Models","display_name":"DiffFuSR: Super-Resolution of All Sentinel-2 Multispectral Bands Using Diffusion Models","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416873282","doi":"https://doi.org/10.1109/tgrs.2025.3638896"},"language":null,"primary_location":{"id":"doi:10.1109/tgrs.2025.3638896","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3638896","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-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/A5078006586","display_name":"Muhammad Sarmad","orcid":"https://orcid.org/0000-0002-8635-9000"},"institutions":[{"id":"https://openalex.org/I144648426","display_name":"Norwegian Computing Center","ror":"https://ror.org/02gm7te43","country_code":"NO","type":"nonprofit","lineage":["https://openalex.org/I144648426"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Muhammad Sarmad","raw_affiliation_strings":["Norwegian Computing Center, Oslo, Norway"],"raw_orcid":"https://orcid.org/0000-0002-8635-9000","affiliations":[{"raw_affiliation_string":"Norwegian Computing Center, Oslo, Norway","institution_ids":["https://openalex.org/I144648426"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023225712","display_name":"Michael Kampffmeyer","orcid":"https://orcid.org/0000-0002-7699-0405"},"institutions":[{"id":"https://openalex.org/I144648426","display_name":"Norwegian Computing Center","ror":"https://ror.org/02gm7te43","country_code":"NO","type":"nonprofit","lineage":["https://openalex.org/I144648426"]},{"id":"https://openalex.org/I78037679","display_name":"UiT The Arctic University of Norway","ror":"https://ror.org/00wge5k78","country_code":"NO","type":"education","lineage":["https://openalex.org/I78037679"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Michael Kampffmeyer","raw_affiliation_strings":["Department of Physics and Technology, UiT The Arctic University of Norway, Troms&#x00F8;, Norway","Norwegian Computing Center, Oslo, Norway"],"raw_orcid":"https://orcid.org/0000-0002-7699-0405","affiliations":[{"raw_affiliation_string":"Department of Physics and Technology, UiT The Arctic University of Norway, Troms&#x00F8;, Norway","institution_ids":["https://openalex.org/I78037679"]},{"raw_affiliation_string":"Norwegian Computing Center, Oslo, Norway","institution_ids":["https://openalex.org/I144648426"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084672445","display_name":"Arnt-B\u00f8rre Salberg","orcid":"https://orcid.org/0000-0002-8113-8460"},"institutions":[{"id":"https://openalex.org/I144648426","display_name":"Norwegian Computing Center","ror":"https://ror.org/02gm7te43","country_code":"NO","type":"nonprofit","lineage":["https://openalex.org/I144648426"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Arnt-B\u00f8rre Salberg","raw_affiliation_strings":["Norwegian Computing Center, Oslo, Norway"],"raw_orcid":"https://orcid.org/0000-0002-8113-8460","affiliations":[{"raw_affiliation_string":"Norwegian Computing Center, Oslo, Norway","institution_ids":["https://openalex.org/I144648426"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5239,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.86580461,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9713000059127808,"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":0.9713000059127808,"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":0.010499999858438969,"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":0.006200000178068876,"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/multispectral-image","display_name":"Multispectral image","score":0.7218000292778015},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6406999826431274},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6029999852180481},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.5444999933242798},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5012999773025513},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.49470001459121704},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.46880000829696655},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45989999175071716},{"id":"https://openalex.org/keywords/spectral-bands","display_name":"Spectral bands","score":0.38199999928474426}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7322999835014343},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7218000292778015},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6621999740600586},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6406999826431274},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6029999852180481},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5666999816894531},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.5444999933242798},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5012999773025513},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.49470001459121704},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48019999265670776},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.46880000829696655},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45989999175071716},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.38199999928474426},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.36239999532699585},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.31459999084472656},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C104541649","wikidata":"https://www.wikidata.org/wiki/Q6935090","display_name":"Multispectral pattern recognition","level":3,"score":0.2669999897480011},{"id":"https://openalex.org/C107445234","wikidata":"https://www.wikidata.org/wiki/Q280995","display_name":"Panchromatic film","level":3,"score":0.2639000117778778},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.25690001249313354},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3638896","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3638896","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5037331601","display_name":null,"funder_award_id":"4000141281","funder_id":"https://openalex.org/F4320318240","funder_display_name":"European Space Agency"}],"funders":[{"id":"https://openalex.org/F4320318240","display_name":"European Space Agency","ror":"https://ror.org/03wd9za21"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W1901129140","https://openalex.org/W2021384698","https://openalex.org/W2087380704","https://openalex.org/W2121058967","https://openalex.org/W2123046940","https://openalex.org/W2171211028","https://openalex.org/W2396656711","https://openalex.org/W2476548250","https://openalex.org/W2768814045","https://openalex.org/W2792142731","https://openalex.org/W2794252992","https://openalex.org/W2891158090","https://openalex.org/W2962785568","https://openalex.org/W2963470893","https://openalex.org/W3035524453","https://openalex.org/W3043884194","https://openalex.org/W3155072588","https://openalex.org/W3168684807","https://openalex.org/W4214848470","https://openalex.org/W4288391574","https://openalex.org/W4312933868","https://openalex.org/W4385757756","https://openalex.org/W4386432174","https://openalex.org/W4386935461","https://openalex.org/W4396941500","https://openalex.org/W4402263930","https://openalex.org/W4405523099","https://openalex.org/W4407591248"],"related_works":[],"abstract_inverted_index":{"This":[0,145],"paper":[1],"presents":[2],"<italic":[3],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[4],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">DiffFuSR</i>,":[5],"a":[6,20,35,58,74,79,148],"modular":[7,150],"pipeline":[8,30,97],"for":[9],"super-resolving":[10],"all":[11],"12":[12],"spectral":[13,116],"bands":[14,67],"of":[15,26,93,113,137],"Sentinel-2":[16,54,152],"Level-2A":[17],"imagery":[18,44],"to":[19,52,87],"unified":[21],"ground":[22],"sampling":[23],"distance":[24],"(GSD)":[25],"2.5":[27],"meters.":[28],"The":[29],"comprises":[31],"two":[32],"stages:":[33],"(i)":[34],"diffusion-based":[36],"super-resolution":[37],"(SR)":[38],"model":[39,82],"trained":[40],"on":[41,98],"high-resolution":[42],"RGB":[43,71],"from":[45],"the":[46,64,69,94,99,104,124],"NAIP":[47],"and":[48,56,83,120,130,141,161,166],"WorldStrat":[49],"datasets,":[50],"harmonized":[51,156],"simulate":[53],"characteristics;":[55],"(ii)":[57],"learned":[59,131],"fusion":[60,125,162],"network":[61,126],"that":[62,103,154],"upscales":[63],"remaining":[65],"multispectral":[66],"using":[68],"super-resolved":[70],"image":[72],"as":[73],"spatial":[75,118],"prior.":[76],"We":[77],"introduce":[78],"robust":[80],"degradation":[81,85],"contrastive":[84],"encoder":[86],"support":[88],"blind":[89],"SR.":[90],"Extensive":[91],"evaluations":[92],"proposed":[95,105],"SR":[96,153],"OpenSR":[100],"benchmark":[101],"demonstrate":[102],"method":[106],"outperforms":[107,128],"current":[108],"SOTA":[109],"baselines":[110],"in":[111],"terms":[112],"reflectance":[114],"fidelity,":[115],"consistency,":[117],"alignment,":[119],"hallucination":[121],"suppression.":[122],"Furthermore,":[123],"significantly":[127],"classical":[129],"pansharpening":[132],"approaches,":[133],"enabling":[134],"accurate":[135],"enhancement":[136],"Sentinel-2\u2019s":[138],"20":[139],"m":[140,143],"60":[142],"bands.":[144],"work":[146],"proposes":[147],"novel":[149],"framework":[151],"utilizes":[155],"learning":[157],"with":[158],"diffusion":[159],"models":[160,167],"strategies.":[163],"Our":[164],"code":[165],"can":[168],"be":[169],"found":[170],"at":[171],"https://github.com/NorskRegnesentral/DiffFuSR.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2025-12-13T23:11:00.310470","created_date":"2025-12-01T00:00:00"}
