Autor: |
Rodney V. Fonseca, Rogerio G. Negri, Aluisio Pinheiro, Abdourrahmane Mahamane Atto |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Předmět: |
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Zdroj: |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 4013-4023 (2023) |
Druh dokumentu: |
article |
ISSN: |
2151-1535 |
DOI: |
10.1109/JSTARS.2023.3268601 |
Popis: |
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. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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