{"id":"https://openalex.org/W4414199267","doi":"https://doi.org/10.1109/jstars.2025.3609966","title":"DWFDA-CD:A Diffusion Model-Based Wavelet Frequency Domain Attention Network for Remote Sensing Change Detection","display_name":"DWFDA-CD:A Diffusion Model-Based Wavelet Frequency Domain Attention Network for Remote Sensing Change Detection","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414199267","doi":"https://doi.org/10.1109/jstars.2025.3609966"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2025.3609966","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3609966","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2025.3609966","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100539901","display_name":"Yunfei Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I83776822","display_name":"Shandong Institute of Business and Technology","ror":"https://ror.org/03rrkrc24","country_code":"CN","type":"education","lineage":["https://openalex.org/I83776822"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunfei Zhu","raw_affiliation_strings":["School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China","institution_ids":["https://openalex.org/I83776822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100880935","display_name":"Dapeng Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I83776822","display_name":"Shandong Institute of Business and Technology","ror":"https://ror.org/03rrkrc24","country_code":"CN","type":"education","lineage":["https://openalex.org/I83776822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dapeng Cheng","raw_affiliation_strings":["School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China","institution_ids":["https://openalex.org/I83776822"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101594883","display_name":"Jinjiang Li","orcid":"https://orcid.org/0009-0009-8155-530X"},"institutions":[{"id":"https://openalex.org/I83776822","display_name":"Shandong Institute of Business and Technology","ror":"https://ror.org/03rrkrc24","country_code":"CN","type":"education","lineage":["https://openalex.org/I83776822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinjiang Li","raw_affiliation_strings":["School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China","institution_ids":["https://openalex.org/I83776822"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100539901"],"corresponding_institution_ids":["https://openalex.org/I83776822"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":1.2803,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85968791,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"18","issue":null,"first_page":"27453","last_page":"27472"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9617000222206116,"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":0.9617000222206116,"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/change-detection","display_name":"Change detection","score":0.6880000233650208},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6435999870300293},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6234999895095825},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6147000193595886},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4878000020980835},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4474000036716461},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.41839998960494995},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.399399995803833},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.3978999853134155}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7516000270843506},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6880000233650208},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6435999870300293},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6234999895095825},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6147000193595886},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5684000253677368},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.557200014591217},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4878000020980835},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4474000036716461},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.41839998960494995},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4108999967575073},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.399399995803833},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.3978999853134155},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.376800000667572},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.3763999938964844},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3481999933719635},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3156000077724457},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3107999861240387},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.3084999918937683},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.29670000076293945},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2694000005722046},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.25540000200271606}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2025.3609966","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3609966","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d8d815d740b247f8a67d9a6169a20e63","is_oa":true,"landing_page_url":"https://doaj.org/article/d8d815d740b247f8a67d9a6169a20e63","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 27453-27472 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2025.3609966","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3609966","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0,66,175],"Remote":[1,14,116],"Sensing":[2,117],"Change":[3,118],"Detection":[4,119],"(RSCD),":[5],"noise":[6,22,51,139,151,196],"is":[7,165,251,276,301,326,346],"a":[8,124,158,179],"key":[9],"factor":[10],"affecting":[11],"detection":[12,64,354,393],"accuracy.":[13,394],"sensing":[15,361],"images":[16],"are":[17,228],"often":[18],"affected":[19],"by":[20,153],"global":[21],"such":[23,52,357],"as":[24,53,233,358],"environmental":[25],"interference,":[26],"sensor":[27],"noise,":[28],"and":[29,39,56,79,85,138,148,192,213,225,244,256,269,281,294,306,319,331,342,345,364,382],"changes":[30,38],"in":[31,75,145],"lighting":[32],"conditions,":[33],"which":[34,164,250,275,300,325],"can":[35],"obscure":[36],"subtle":[37],"lead":[40],"to":[41,128,171,186],"misjudgments":[42],"or":[43],"missed":[44],"detections.":[45],"At":[46],"the":[47,63,168,220,223,378],"same":[48],"time,":[49],"local":[50,150],"object":[54],"edges":[55],"building":[57,212],"shadows":[58],"may":[59],"also":[60],"interfere":[61],"with":[62,81,352],"process.":[65],"recent":[67],"years,":[68],"diffusion":[69,106,384],"models":[70],"have":[71],"made":[72],"significant":[73],"progress":[74],"data":[76],"distribution":[77],"modeling":[78],"denoising,":[80],"their":[82],"gradual":[83],"generation":[84],"denoising":[86,169],"mechanisms":[87],"providing":[88],"new":[89],"solutions":[90],"for":[91,115,349],"change":[92,190,216],"detection.":[93],"To":[94,141,368],"address":[95],"these":[96],"challenges,":[97],"this":[98,155],"paper":[99,156],"proposes":[100],"an":[101,239,245,252,264,270,277,289,295,302,314,320,327],"end-to-end":[102],"framework":[103,122],"based":[104],"on":[105,189,207,219,260,285,310,340,376],"models-A":[107],"Diffusion":[108],"Model-based":[109],"Wavelet":[110,159],"Frequency":[111],"Domain":[112],"Attention":[113],"Network":[114],"(DWFDA-CD).":[120],"This":[121,335],"integrates":[123],"weight-sharing":[125],"feature":[126],"encoder":[127],"extract":[129],"shallow":[130],"features":[131,144],"from":[132],"dual-time":[133],"images,":[134],"reducing":[135],"redundant":[136],"information":[137],"propagation.":[140],"enhance":[142],"edge":[143,173],"complex":[146],"backgrounds":[147],"reduce":[149],"caused":[152],"shadows,":[154],"introduces":[157],"Detail":[160],"Enhancement":[161],"Module":[162,184],"(WDEM),":[163],"embedded":[166],"into":[167],"process":[170],"improve":[172,370],"sensitivity.":[174],"addition,":[176],"we":[177,237,262,287,312],"design":[178],"Multilevel":[180],"Differential":[181],"Feature":[182],"Extraction":[183],"(MDFEM)":[185],"precisely":[187],"focus":[188,375],"areas":[191],"suppress":[193],"irrelevant":[194],"background":[195],"interference.":[197],"The":[198],"experimental":[199],"results":[200],"show":[201],"that":[202],"DWFDA-CD":[203],"significantly":[204,387],"improves":[205],"performance":[206],"four":[208,221],"public":[209],"datasets":[210],"(including":[211],"land":[214],"use":[215],"detection).":[217],"Specifically,":[218],"datasets,":[222],"F1":[224,240,265,290,315],"IoU":[226,246,271,296,321],"metrics":[227],"improved":[229],"over":[230,258,283,308,333],"state-of-the-art":[231],"methods":[232],"follows:":[234],"On":[235],"LEVIR,":[236],"achieved":[238,263,288,313],"score":[241,247,266,272,291,297,316,322],"of":[242,248,254,267,273,279,292,298,304,317,323,329],"91.72%":[243],"84.69%,":[249],"improvement":[253,278,303,328],"0.45%":[255],"0.75%":[257],"Changer;":[259],"WHU,":[261],"93.64%":[268],"88.03%,":[274],"1.10%":[280],"1.51%":[282],"GCD-DDPM;":[284,309],"GZ,":[286],"87.96%":[293],"78.51%,":[299],"1.76%":[305],"2.76%":[307],"CDD,":[311],"96.06%":[318],"92.42%,":[324],"1.13%":[330],"1.86%":[332],"GCD-DDPM.":[334],"method":[336],"has":[337],"high":[338],"demands":[339],"computational":[341,389],"storage":[343],"resources,":[344],"especially":[347],"suitable":[348],"application":[350],"scenarios":[351],"strict":[353],"accuracy":[355],"requirements,":[356],"high-resolution":[359],"remote":[360],"image":[362],"processing":[363],"large-scale":[365],"dataset":[366],"analysis.":[367],"further":[369],"practicality,":[371],"future":[372],"research":[373],"will":[374],"optimizing":[377],"channel":[379],"pruning":[380],"strategy":[381],"adaptive":[383],"sampling":[385],"mechanism,":[386],"enhancing":[388],"efficiency":[390],"while":[391],"ensuring":[392]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}