{"id":"https://openalex.org/W2791873954","doi":"https://doi.org/10.3390/rs10020355","title":"Matching of Remote Sensing Images with Complex Background Variations via Siamese Convolutional Neural Network","display_name":"Matching of Remote Sensing Images with Complex Background Variations via Siamese Convolutional Neural Network","publication_year":2018,"publication_date":"2018-02-24","ids":{"openalex":"https://openalex.org/W2791873954","doi":"https://doi.org/10.3390/rs10020355","mag":"2791873954"},"language":"en","primary_location":{"id":"doi:10.3390/rs10020355","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10020355","pdf_url":"https://www.mdpi.com/2072-4292/10/2/355/pdf?version=1519540053","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/10/2/355/pdf?version=1519540053","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031680851","display_name":"Haiqing He","orcid":"https://orcid.org/0000-0001-9361-0219"},"institutions":[{"id":"https://openalex.org/I4210119674","display_name":"East China University of Technology","ror":"https://ror.org/027385r44","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119674"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haiqing He","raw_affiliation_strings":["School of Geomatics, East China University of Technology, Nanchang 330013, China"],"affiliations":[{"raw_affiliation_string":"School of Geomatics, East China University of Technology, Nanchang 330013, China","institution_ids":["https://openalex.org/I4210119674"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100337209","display_name":"Min Chen","orcid":"https://orcid.org/0000-0002-0960-4447"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Chen","raw_affiliation_strings":["Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100443173","display_name":"Ting Chen","orcid":"https://orcid.org/0000-0001-8414-6346"},"institutions":[{"id":"https://openalex.org/I4210119674","display_name":"East China University of Technology","ror":"https://ror.org/027385r44","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Chen","raw_affiliation_strings":["School of Water Resources & Environmental Engineering, East China University of Technology, Nanchang 330013, China"],"affiliations":[{"raw_affiliation_string":"School of Water Resources & Environmental Engineering, East China University of Technology, Nanchang 330013, China","institution_ids":["https://openalex.org/I4210119674"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108866505","display_name":"Dajun Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119674","display_name":"East China University of Technology","ror":"https://ror.org/027385r44","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119674"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dajun Li","raw_affiliation_strings":["School of Geomatics, East China University of Technology, Nanchang 330013, China"],"affiliations":[{"raw_affiliation_string":"School of Geomatics, East China University of Technology, Nanchang 330013, China","institution_ids":["https://openalex.org/I4210119674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5031680851"],"corresponding_institution_ids":["https://openalex.org/I4210119674"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":4.4621,"has_fulltext":false,"cited_by_count":77,"citation_normalized_percentile":{"value":0.960917,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"10","issue":"2","first_page":"355","last_page":"355"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9993000030517578,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9939000010490417,"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/T12983","display_name":"Satellite Image Processing and Photogrammetry","score":0.9868999719619751,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7602134943008423},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.743277907371521},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.689944326877594},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6257488131523132},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5918589234352112},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.556126058101654},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5236482620239258},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.5168079137802124},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45974642038345337},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4492359459400177},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.4375104010105133},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.43275317549705505},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22048383951187134}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7602134943008423},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.743277907371521},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.689944326877594},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6257488131523132},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5918589234352112},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.556126058101654},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5236482620239258},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.5168079137802124},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45974642038345337},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4492359459400177},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.4375104010105133},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.43275317549705505},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22048383951187134},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs10020355","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10020355","pdf_url":"https://www.mdpi.com/2072-4292/10/2/355/pdf?version=1519540053","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:72b16612da3d4d45aa1723dcb769c4ac","is_oa":true,"landing_page_url":"https://doaj.org/article/72b16612da3d4d45aa1723dcb769c4ac","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 10, Iss 2, p 355 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/10/2/355/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs10020355","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs10020355","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10020355","pdf_url":"https://www.mdpi.com/2072-4292/10/2/355/pdf?version=1519540053","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3236820748","display_name":null,"funder_award_id":"41401526 and 41501492","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G9115767","display_name":null,"funder_award_id":"2016YFB0502603","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2791873954.pdf","grobid_xml":"https://content.openalex.org/works/W2791873954.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1591388113","https://openalex.org/W1836465849","https://openalex.org/W1869500417","https://openalex.org/W1928419358","https://openalex.org/W1955055330","https://openalex.org/W1963623641","https://openalex.org/W1984434739","https://openalex.org/W1993929638","https://openalex.org/W1998680950","https://openalex.org/W2008789742","https://openalex.org/W2052094314","https://openalex.org/W2053430949","https://openalex.org/W2083358477","https://openalex.org/W2085261163","https://openalex.org/W2085851460","https://openalex.org/W2088667706","https://openalex.org/W2089888558","https://openalex.org/W2119605622","https://openalex.org/W2124386111","https://openalex.org/W2133584444","https://openalex.org/W2145072179","https://openalex.org/W2147237076","https://openalex.org/W2147555557","https://openalex.org/W2177274842","https://openalex.org/W2340296683","https://openalex.org/W2394916924","https://openalex.org/W2467594225","https://openalex.org/W2552065934","https://openalex.org/W2572013555","https://openalex.org/W2607603241","https://openalex.org/W2608922915","https://openalex.org/W2624172411","https://openalex.org/W2746837200","https://openalex.org/W3125412419","https://openalex.org/W6676770471"],"related_works":["https://openalex.org/W2022849497","https://openalex.org/W3081299480","https://openalex.org/W2407190427","https://openalex.org/W2919210741","https://openalex.org/W2907584218","https://openalex.org/W3002446410","https://openalex.org/W1691631808","https://openalex.org/W1586320973","https://openalex.org/W4390224712","https://openalex.org/W4322096758"],"abstract_inverted_index":{"Feature-based":[0],"matching":[1,11,90,125,175,304,320],"methods":[2,30,60],"have":[3,61],"been":[4,62],"widely":[5],"used":[6,45,190,255,282],"in":[7,71,79,100,179,353],"remote":[8,87,308],"sensing":[9,88,309],"image":[10,20,42,54,72,89,165],"given":[12],"their":[13],"capability":[14],"to":[15,46,53,110,172,191,207,237,256,283],"achieve":[16],"excellent":[17],"performance":[18,286,305],"despite":[19],"geometric":[21],"and":[22,69,115,126,139,176,218,248,273,344],"radiometric":[23],"distortions.":[24],"However,":[25],"most":[26],"of":[27,124,137,154,196,214,232,265,287,306,332,355],"the":[28,38,48,76,93,113,116,132,148,161,174,180,193,211,215,230,233,239,243,249,261,285,288,296,303,318,325],"feature-based":[29],"are":[31,145,221,254,281],"unreliable":[32],"for":[33,65,86],"complex":[34,278,312],"background":[35,55,279,313],"variations,":[36,314],"because":[37],"gradient":[39],"or":[40],"other":[41,342],"grayscale":[43],"information":[44],"construct":[47],"feature":[49,67],"descriptor":[50],"is":[51,98,108,157,170,189,205,235,315],"sensitive":[52],"variations.":[56],"Recently,":[57],"deep":[58,80],"learning-based":[59],"proven":[63],"suitable":[64],"high-level":[66],"representation":[68],"comparison":[70],"matching.":[73,166],"Inspired":[74],"by":[75],"progresses":[77],"made":[78],"learning,":[81],"a":[82,104,184,200,225,329,346],"new":[83],"technical":[84],"framework":[85],"based":[91,159,228],"on":[92,160,229],"Siamese":[94],"convolutional":[95,138,155],"neural":[96],"network":[97,106],"presented":[99],"this":[101],"paper.":[102],"First,":[103],"Siamese-type":[105],"architecture":[107],"designed":[109,150],"simultaneously":[111],"learn":[112],"features":[114],"corresponding":[117],"similarity":[118,226],"metric":[119],"from":[120],"labeled":[121],"training":[122],"examples":[123],"non-matching":[127,177],"true-color":[128],"patch":[129],"pairs.":[130],"In":[131,260,322],"proposed":[133,289,297,326],"network,":[134],"two":[135],"streams":[136],"pooling":[140],"layers":[141,156],"sharing":[142],"identical":[143],"weights":[144],"arranged":[146],"without":[147],"manually":[149],"features.":[151],"The":[152,167,291],"number":[153,331],"determined":[158],"factors":[162],"that":[163,295],"affect":[164],"sigmoid":[168,234],"function":[169],"employed":[171],"compute":[173],"probabilities":[178],"output":[181,231],"layer.":[182],"Second,":[183],"gridding":[185],"sub-pixel":[186],"Harris":[187],"algorithm":[188,247],"obtain":[192],"accurate":[194],"localization":[195],"candidate":[197,216],"matches.":[198,241,259],"Third,":[199],"Gaussian":[201],"pyramid":[202],"coupling":[203],"quadtree":[204],"adopted":[206,236],"gradually":[208],"narrow":[209],"down":[210],"searching":[212],"space":[213],"matches,":[217],"multiscale":[219],"patches":[220],"compared":[222],"synchronously.":[223],"Subsequently,":[224],"measure":[227],"find":[238],"initial":[240],"Finally,":[242],"random":[244],"sample":[245],"consensus":[246],"whole-to-local":[250],"quadratic":[251],"polynomial":[252],"constraints":[253],"remove":[257],"false":[258],"experiments,":[262,324],"different":[263],"types":[264],"satellite":[266],"datasets,":[267],"such":[268],"as":[269],"ZY3,":[270],"GF1,":[271],"IKONOS,":[272],"Google":[274],"Earth":[275],"images,":[276],"with":[277,311],"variations":[280],"evaluate":[284],"method.":[290],"experimental":[292],"results":[293],"demonstrate":[294],"method,":[298],"which":[299],"can":[300],"significantly":[301],"improve":[302],"multi-temporal":[307],"images":[310],"better":[316],"than":[317,341,350],"state-of-the-art":[319],"methods.":[321],"our":[323],"method":[327],"obtained":[328],"large":[330],"evenly":[333],"distributed":[334],"matches":[335],"(at":[336],"least":[337],"10":[338],"times":[339],"more":[340],"methods)":[343],"achieved":[345],"high":[347],"accuracy":[348],"(less":[349],"1":[351],"pixel":[352],"terms":[354],"root":[356],"mean":[357],"square":[358],"error).":[359]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":14}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}