Wavelet Spatio-Temporal Change Detection on Multitemporal SAR Images

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorWeizmann Institute of Science-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade Estadual de Campinas (UNICAMP)-
Autor(es): dc.contributorListic - Polytech Annecy-Chambéry-
Autor(es): dc.creatorFonseca, Rodney V.-
Autor(es): dc.creatorNegri, Rogerio G.-
Autor(es): dc.creatorPinheiro, Aluisio-
Autor(es): dc.creatorAtto, Abdourrahmane Mahamane-
Data de aceite: dc.date.accessioned2025-08-21T23:37:09Z-
Data de disponibilização: dc.date.available2025-08-21T23:37:09Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2022-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/JSTARS.2023.3268601-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/247255-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/247255-
Descrição: dc.descriptionIn this article, we introduce the wavelet energies correlation screening (WECS), an unsupervised method to detect spatio-temporal changes on multitemporal SAR images. The procedure is based on wavelet approximation for the multitemporal images, wavelet energy apportionment, and ultrahigh-dimensional correlation screening for the wavelet coefficients. We show WECS's performance on simulated multitemporal image data. We also evaluate the proposed method on a time series of 85 Sentinel-1 images of a forest region at the border of Brazil and French Guiana. Comparisons with well-known change detection methods found in the literature highlight the proposal's superiority in terms of change detection accuracy. Additionally, the introduced method has simple architecture and low computational cost.-
Descrição: dc.descriptionWeizmann Institute of Science Department of Computer Science and Applied Mathematics-
Descrição: dc.descriptionSão Paulo State University Department of Environmental Engineering-
Descrição: dc.descriptionUniversity of Campinas Department of Statistics-
Descrição: dc.descriptionUniversité de Savoie Listic - Polytech Annecy-Chambéry-
Descrição: dc.descriptionSão Paulo State University Department of Environmental Engineering-
Formato: dc.format4013-4023-
Idioma: dc.languageen-
Relação: dc.relationIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectChange detection-
Palavras-chave: dc.subjectmultitemporal images-
Palavras-chave: dc.subjectremote sensing-
Palavras-chave: dc.subjectsimulated images-
Palavras-chave: dc.subjectwavelets-
Título: dc.titleWavelet Spatio-Temporal Change Detection on Multitemporal SAR Images-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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