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One of the fundamental problems in Synthetic Aperture Radar (SAR) imaging is phase errors. Phase errors occur when the time required for the transmitted signal from SAR to the target and back cannot be obtained properly either because the distance between the SAR platform and the target cannot be measured exactly or in the case of random delays in the signal due to propagation in atmospheric turbulence...
We propose a sparse signal representation-based method for complex-valued imaging. Many coherent imaging systems such as synthetic aperture radar (SAR) have an inherent random phase, complex-valued nature. On the other hand sparse signal representation, which has mostly been exploited in real-valued problems, has many capabilities such as superresolution and feature enhancement for various reconstruction...
We propose a shape and data driven texture segmentation method using local binary patterns (LBP) and active contours. In particular, we pass textured images through a new LBP-based filter, which produces non-textured images. In this "filtered" domain each textured region of the original image exhibits a characteristic intensity distribution. In this domain we pose the segmentation problem...
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