{"id":"https://openalex.org/W7125524765","doi":"https://doi.org/10.3390/jimaging12010052","title":"Multi-Frequency GPR Image Fusion Based on Convolutional Sparse Representation to Enhance Road Detection","display_name":"Multi-Frequency GPR Image Fusion Based on Convolutional Sparse Representation to Enhance Road Detection","publication_year":2026,"publication_date":"2026-01-22","ids":{"openalex":"https://openalex.org/W7125524765","doi":"https://doi.org/10.3390/jimaging12010052","pmid":"https://pubmed.ncbi.nlm.nih.gov/41590937"},"language":"en","primary_location":{"id":"doi:10.3390/jimaging12010052","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging12010052","pdf_url":"https://www.mdpi.com/2313-433X/12/1/52/pdf?version=1769072832","source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"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":"Journal of Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2313-433X/12/1/52/pdf?version=1769072832","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114189357","display_name":"Liang Fang","orcid":"https://orcid.org/0009-0005-5852-5402"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liang Fang","raw_affiliation_strings":["School of Artificial Intelligence, China University of Mining and Technology (Beijing), Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, China University of Mining and Technology (Beijing), Beijing 100083, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123684148","display_name":"Feng Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Yang","raw_affiliation_strings":["School of Artificial Intelligence, China University of Mining and Technology (Beijing), Beijing 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, China University of Mining and Technology (Beijing), Beijing 100083, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123651291","display_name":"Yuanjing Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanjing Fang","raw_affiliation_strings":["School of Artificial Intelligence, China University of Mining and Technology (Beijing), Beijing 100083, China"],"raw_orcid":"https://orcid.org/0009-0003-3319-3718","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, China University of Mining and Technology (Beijing), Beijing 100083, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058882524","display_name":"Junli Nie","orcid":null},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junli Nie","raw_affiliation_strings":["Guizhou University, Guiyang 550025, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guizhou University, Guiyang 550025, China","institution_ids":["https://openalex.org/I178232147"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5114189357"],"corresponding_institution_ids":["https://openalex.org/I25757504"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":11.9696,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.96057292,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"12","issue":"1","first_page":"52","last_page":"52"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.944599986076355,"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"}},"topics":[{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.944599986076355,"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"}},{"id":"https://openalex.org/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.022199999541044235,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.007799999788403511,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/ground-penetrating-radar","display_name":"Ground-penetrating radar","score":0.8794000148773193},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5259000062942505},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5030999779701233},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44589999318122864},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.43709999322891235},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4345000088214874},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.43309998512268066},{"id":"https://openalex.org/keywords/ringing","display_name":"Ringing","score":0.4156000018119812}],"concepts":[{"id":"https://openalex.org/C71813955","wikidata":"https://www.wikidata.org/wiki/Q503560","display_name":"Ground-penetrating radar","level":3,"score":0.8794000148773193},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.767300009727478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7468000054359436},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5519000291824341},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5259000062942505},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5030999779701233},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44589999318122864},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.43709999322891235},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4345000088214874},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.43309998512268066},{"id":"https://openalex.org/C30684385","wikidata":"https://www.wikidata.org/wiki/Q176509","display_name":"Ringing","level":3,"score":0.4156000018119812},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.39800000190734863},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3792000114917755},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.36820000410079956},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.32100000977516174},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.2808000147342682},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.25540000200271606}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/jimaging12010052","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging12010052","pdf_url":"https://www.mdpi.com/2313-433X/12/1/52/pdf?version=1769072832","source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"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":"Journal of Imaging","raw_type":"journal-article"},{"id":"pmid:41590937","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41590937","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of imaging","raw_type":null},{"id":"pmh:oai:doaj.org/article:4e3031decf17439ba783271ef3fc3875","is_oa":true,"landing_page_url":"https://doaj.org/article/4e3031decf17439ba783271ef3fc3875","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Imaging, Vol 12, Iss 1, p 52 (2026)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12843019","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12843019/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"J Imaging","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/jimaging12010052","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging12010052","pdf_url":"https://www.mdpi.com/2313-433X/12/1/52/pdf?version=1769072832","source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"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":"Journal of Imaging","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G156000567","display_name":null,"funder_award_id":"2021YFC3090304","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5357851806","display_name":null,"funder_award_id":"52427901","funder_id":"https://openalex.org/F4320311026","funder_display_name":"Shandong University"},{"id":"https://openalex.org/G608158825","display_name":null,"funder_award_id":"42264008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6559934287","display_name":null,"funder_award_id":"2021YFC3090303","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320311026","display_name":"Shandong University","ror":"https://ror.org/0207yh398"},{"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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7125524765.pdf","grobid_xml":"https://content.openalex.org/works/W7125524765.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1648310879","https://openalex.org/W2047652678","https://openalex.org/W2112458404","https://openalex.org/W2160547390","https://openalex.org/W2168783614","https://openalex.org/W2190662802","https://openalex.org/W2313224414","https://openalex.org/W2529729362","https://openalex.org/W2532801510","https://openalex.org/W2891220496","https://openalex.org/W2917480588","https://openalex.org/W2981398465","https://openalex.org/W3021118108","https://openalex.org/W3043449013","https://openalex.org/W3139399265","https://openalex.org/W3152512474","https://openalex.org/W3185007799","https://openalex.org/W4281657510","https://openalex.org/W4281681804","https://openalex.org/W4386163346","https://openalex.org/W4388348551","https://openalex.org/W4401921626"],"related_works":[],"abstract_inverted_index":{"Single-frequency":[0],"ground":[1],"penetrating":[2],"radar":[3],"(GPR)":[4],"systems":[5],"are":[6,63],"fundamentally":[7],"constrained":[8],"by":[9],"a":[10,32,56],"trade-off":[11],"between":[12],"penetration":[13,114],"depth":[14],"and":[15,22,52,79,102,133],"resolution,":[16],"alongside":[17],"issues":[18],"like":[19],"narrow":[20],"bandwidth":[21],"ringing":[23],"interference.":[24],"To":[25],"break":[26],"this":[27],"limitation,":[28],"we":[29],"have":[30],"developed":[31],"multi-frequency":[33,49],"data":[34,104],"fusion":[35,91,109],"technique":[36],"grounded":[37],"in":[38,129],"convolutional":[39,61],"sparse":[40],"representation":[41],"(CSR).":[42],"The":[43],"proposed":[44],"methodology":[45],"involves":[46],"spatially":[47],"registering":[48],"GPR":[50,68,130],"signals":[51],"fusing":[53],"them":[54],"via":[55],"CSR":[57],"framework,":[58],"where":[59],"the":[60,84,112,119],"dictionaries":[62],"derived":[64],"from":[65],"simulated":[66,101],"high-definition":[67],"data.":[69],"Extensive":[70],"evaluation":[71],"using":[72],"information":[73,81],"entropy,":[74],"average":[75],"gradient,":[76],"mutual":[77],"information,":[78],"visual":[80],"fidelity":[82],"demonstrates":[83],"superiority":[85],"of":[86,115,122],"our":[87,107],"method":[88],"over":[89],"traditional":[90],"approaches":[92],"(e.g.,":[93],"weighted":[94],"average,":[95],"PCA,":[96],"2D":[97],"wavelets).":[98],"Tests":[99],"on":[100],"real":[103],"confirm":[105],"that":[106],"CSR-based":[108],"successfully":[110],"synergizes":[111],"deep":[113],"low":[116],"frequencies":[117],"with":[118],"fine":[120],"resolution":[121],"high":[123],"frequencies,":[124],"leading":[125],"to":[126],"substantial":[127],"gains":[128],"image":[131],"clarity":[132],"interpretability.":[134]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-01-24T00:00:00"}