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Reliable automatic ship detection in Synthetic Aperture Radar (SAR) imagery plays an important role in the surveillance of maritime activity. Apart from the well-known Spectral Residual (SR) and CFAR detector, there has emerged a novel method for SAR ship detection, based on the deep learning features. Within this paper, we present a framework of Sea-Land Segmentation-based Convolutional Neural Network...
We present a registration algorithm for automatic, robust SAR (Synthetic Aperture Radar) image alignment. The registration problem is handled using sparse feature representation, which comprises local feature localization and description. The feature location is determined by detecting bifurcation structure in edge image and its orientation is assigned using corresponding bifurcation structure type...
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