Wavelet Spatio-Temporal Change Detection on Multitemporal SAR Images

• Autor(a) principal: Fonseca, Rodney V.
• Data de Publicação: 2023
• Outros Autores: Negri, Rogerio G. [UNESP], Pinheiro, Aluisio, Atto, Abdourrahmane Mahamane
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1109/JSTARS.2023.3268601; http://hdl.handle.net/11449/247255
• topic: Change detection; multitemporal images; remote sensing; simulated images; wavelets

In 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.