Abstract
This paper presents despeckling of Synthetic Aperture Radar (SAR) detected data using deep convolutional networks. A discriminative model learning using a deep convolutional neural network (DCNN) was used. A DCNN was used to learn speckle statistical properties to process SAR data. The idea is to use two identical subnetworks, very similar to Siamese deep neural networks , which consisted of 15 layers. The network used a residual learning strategy using a large SAR database. SAR images were multilooked in order to model a noiseless SAR images. Experimental results demonstrated promising results using synthetic and real images.
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