Wavelet Spatio-Temporal Change Detection on multi-temporal PolSAR images

Abstract

We introduce WECS (Wavelet Energies Correlation Sreening), an unsupervised sparse procedure to detect spatio-temporal change points on multi-temporal SAR (POLSAR) images or even on sequences of very high resolution images. The procedure is based on wavelet approximation for the multi-temporal images, wavelet energy apportionment, and ultra-high dimensional correlation screening for the wavelet coefficients. We present two complimentary wavelet measures in order to detect sudden and/or cumulative changes, as well as for the case of stationary or non-stationary multi-temporal images. We show WECS performance on synthetic multi-temporal image data. We also apply the proposed method to a time series of 85 satellite images in the border region of Brazil and the French Guiana. The images were captured from November 08, 2015 to December 09 2017.