{"id":"https://openalex.org/W4415883265","doi":"https://doi.org/10.1109/tgrs.2025.3628638","title":"RGBT Fusion-Based Airborne Synthetic Aperture Occlusion Removal Target Imaging","display_name":"RGBT Fusion-Based Airborne Synthetic Aperture Occlusion Removal Target Imaging","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415883265","doi":"https://doi.org/10.1109/tgrs.2025.3628638"},"language":null,"primary_location":{"id":"doi:10.1109/tgrs.2025.3628638","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3628638","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":null,"display_name":"Yuan Yue","orcid":"https://orcid.org/0009-0009-4327-0848"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuan Yue","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083602794","display_name":"Chunna Tian","orcid":"https://orcid.org/0000-0002-3217-0368"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunna Tian","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101963731","display_name":"Zhiwei Jiang","orcid":"https://orcid.org/0000-0001-7314-2083"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Jiang","raw_affiliation_strings":["School of Physics, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Physics, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106941640","display_name":"Xiangyang Li","orcid":"https://orcid.org/0009-0003-8540-6009"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyang Li","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074841621","display_name":"Shiguo Chen","orcid":"https://orcid.org/0009-0004-1626-8228"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiguo Chen","raw_affiliation_strings":["School of Physics, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Physics, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029708834","display_name":"Dibo Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongliang Hou","raw_affiliation_strings":["School of Telecommunications Engineering, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Telecommunications Engineering, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40592024,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.35409998893737793,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.35409998893737793,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11133","display_name":"UAV Applications and Optimization","score":0.14869999885559082,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.11060000211000443,"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/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.7114999890327454},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.6805999875068665},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4675999879837036},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4375999867916107},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.42289999127388},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.41429999470710754},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.38510000705718994},{"id":"https://openalex.org/keywords/inverse-synthetic-aperture-radar","display_name":"Inverse synthetic aperture radar","score":0.3711000084877014},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3610999882221222}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7594000101089478},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.7114999890327454},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7080000042915344},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.6805999875068665},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6769000291824341},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4675999879837036},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4375999867916107},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.41429999470710754},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.38510000705718994},{"id":"https://openalex.org/C109094680","wikidata":"https://www.wikidata.org/wiki/Q6060432","display_name":"Inverse synthetic aperture radar","level":4,"score":0.3711000084877014},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3610999882221222},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3370000123977661},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C117623542","wikidata":"https://www.wikidata.org/wiki/Q621974","display_name":"Automatic target recognition","level":3,"score":0.32260000705718994},{"id":"https://openalex.org/C78336883","wikidata":"https://www.wikidata.org/wiki/Q4779385","display_name":"Aperture (computer memory)","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.310699999332428},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C181255713","wikidata":"https://www.wikidata.org/wiki/Q7662740","display_name":"Synthetic aperture sonar","level":3,"score":0.2978000044822693},{"id":"https://openalex.org/C2779726219","wikidata":"https://www.wikidata.org/wiki/Q7685884","display_name":"Target acquisition","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.28769999742507935},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.27950000762939453},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.2653000056743622},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2615000009536743}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3628638","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3628638","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/G4752383838","display_name":null,"funder_award_id":"No. 62173265","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4874360938","display_name":null,"funder_award_id":"No. F024020021","funder_id":"https://openalex.org/F4320322857","funder_display_name":"Aeronautical Science Foundation of China"},{"id":"https://openalex.org/G5855802734","display_name":null,"funder_award_id":"202410701213","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6360230148","display_name":null,"funder_award_id":"No. 202410701213","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8494200937","display_name":null,"funder_award_id":"62173265","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/F4320322857","display_name":"Aeronautical Science Foundation of China","ror":"https://ror.org/02wq41p38"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1578285471","https://openalex.org/W1995875735","https://openalex.org/W2047870694","https://openalex.org/W2102593897","https://openalex.org/W2108900252","https://openalex.org/W2111216493","https://openalex.org/W2121274305","https://openalex.org/W2131925136","https://openalex.org/W2145023731","https://openalex.org/W2153125455","https://openalex.org/W2256168994","https://openalex.org/W2471962767","https://openalex.org/W2528330729","https://openalex.org/W2556556019","https://openalex.org/W2887312581","https://openalex.org/W2919115771","https://openalex.org/W2941286517","https://openalex.org/W2957875198","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W3023712671","https://openalex.org/W3046194589","https://openalex.org/W3087637003","https://openalex.org/W3175099349","https://openalex.org/W3213472242","https://openalex.org/W4220893768","https://openalex.org/W4303649263","https://openalex.org/W4312052673","https://openalex.org/W4315485213","https://openalex.org/W4361212918","https://openalex.org/W4382135822","https://openalex.org/W4385245566","https://openalex.org/W4386076504","https://openalex.org/W4386492595","https://openalex.org/W4387789917","https://openalex.org/W4390480888","https://openalex.org/W4390872797","https://openalex.org/W4402571616","https://openalex.org/W4403864711","https://openalex.org/W4405755299"],"related_works":[],"abstract_inverted_index":{"Drones":[0],"are":[1,31],"gaining":[2],"increasing":[3],"popularity":[4],"in":[5,56,163],"bush":[6],"search":[7],"and":[8,28,36,50,112],"rescue":[9],"operations,":[10],"where":[11],"enhancing":[12],"the":[13,23,54,131,139,150],"accuracy":[14],"of":[15],"occluded":[16,63,90],"target":[17,55,64,106,132,153,159,176],"detection":[18,43],"is":[19,58],"crucial":[20],"to":[21,88,117,129,155],"finding":[22],"targets.":[24,91],"However,":[25],"airborne":[26],"LiDAR":[27],"multispectral":[29],"cameras":[30],"limited":[32],"by":[33],"cost,":[34],"efficiency,":[35],"imaging":[37,57,87,177],"quality,":[38],"while":[39],"RGB-":[40],"or":[41],"thermal-based":[42],"methods":[44],"rely":[45],"heavily":[46],"on":[47,102],"model":[48],"performance":[49],"prior":[51],"knowledge.":[52],"Recovering":[53],"a":[59,69,95],"new":[60],"frontier":[61],"for":[62,77],"perception.":[65],"Here,":[66],"we":[67,93,124,143],"propose":[68,94],"novel":[70],"Synthetic":[71,145],"Aperture":[72,146],"Fusion":[73],"Imaging":[74,147],"(SAFI)":[75],"method":[76],"drones,":[78],"combining":[79],"an":[80,157],"RGBT":[81,97],"fusion":[82,98,121],"network":[83],"with":[84,133,178],"synthetic":[85],"aperture":[86],"recover":[89],"Firstly,":[92],"Color-contrast":[96],"Network":[99],"(C-RGBTNet)":[100],"based":[101],"transformer.":[103],"C-RGBTNet":[104],"captures":[105],"thermal":[107,110,135],"features":[108,116],"from":[109,138],"images":[111],"assigns":[113],"RGB":[114],"color":[115,127],"occlusions,":[118],"generating":[119],"high-quality":[120,175],"images.":[122],"Then,":[123],"apply":[125],"HSV-based":[126],"segmentation":[128],"isolate":[130],"strong":[134],"intensity":[136],"(high-brightness)":[137],"cluttered":[140],"background.":[141],"Finally,":[142],"perform":[144],"(SAI),":[148],"synthesizing":[149],"different":[151],"segmented":[152],"parts":[154],"yield":[156],"occlusion-free":[158],"image.":[160],"Experimental":[161],"results":[162],"our":[164],"home-brew":[165],"Downward-view":[166],"Multimodal":[167],"Bush":[168],"(DMB)":[169],"dataset":[170],"demonstrate":[171],"that":[172],"SAFI":[173],"achieves":[174],"effective":[179],"occlusion":[180],"removal,":[181],"significantly":[182],"outperforming":[183],"traditional":[184],"methods.":[185]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-04T00:00:00"}
