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Change detection is an important issue in many applications. In this study, we propose a new change detector for multi-temporal polarimetric synthetic aperture radar (SAR) images. The new detector is based on the optimization of polarimetric contrast minimization. The optimized solution of the contrast model is also given. Experiments are performed on two RADARSAT-2 data sets and results show agreement...
In this paper, a novel change detection method learned from Recurrent Neural Network with transferable ability is proposed. The proposed method, which is based on an improved Long Short Term Memory (LSTM) model, aims at: 1) learning a novel change detection rule to distinguish changed regions with high accuracy; 2) analyzing a new target data with transferable ability from learned change rule; 3)...
This paper presents a method for strong scatterers change detection in synthetic aperture radar (SAR) images based on a decomposition for multi-temporal series. The formulated decomposition model jointly estimates the background of the series and the scatterers. The decomposition model retrieves possible changes in scatterers and the date at which they occurred. An exact optimization method of the...
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