A review of deep-learning techniques for SAR image restoration
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Figure
![Fig. 2. Restoration of the single-look Sentinel-1 image shown in (a) with deep-learning methods illustrative of the 3 training strategies shown in Fig.1: (b) SAR2SAR [1] uses a supervised training strategy (here, the training is performed on synthetic spec](https://thumb-eu.123doks.com/thumbv2/123doknet/11292597.280884/4.918.180.731.103.442/restoration-sentinel-learning-illustrative-strategies-supervised-performed-synthetic.webp)
![Fig. 3. MuLog [11] is one of the first approaches to apply deep neural networks to speckle reduction in polarimetric and interferometric SAR restoration](https://thumb-eu.123doks.com/thumbv2/123doknet/11292597.280884/5.918.82.449.106.331/mulog-approaches-networks-speckle-reduction-polarimetric-interferometric-restoration.webp)
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