Karakus, Oktay ORCID: https://orcid.org/0000-0001-8009-9319 and Achim, Alin 2020. AssenSAR wake detector. University of Bristol. Available at: http://doi.org/10.5523/BRIS.F2Q4T5PQLIX62SV5NTVQ51... |
Official URL: http://doi.org/10.5523/BRIS.F2Q4T5PQLIX62SV5NTVQ51...
Abstract
This code implements a method for detecting ship wakes in synthetic aperture radar (SAR) images of the sea surface. The method is based on a linear model assumption for the wakes and hence the Radon transform is employed, within an inverse problem formulation, for detecting the wakes. The cost function associated with the image formation model includes a sparsity enforcing penalty, i.e., the generalized minimax concave (GMC) function. Despite being a nonconvex function, the GMC penalty allows the overall cost function to remain convex. The proposed solution is based on a Bayesian formulation, whereby the point estimates are recovered using a maximum a posteriori (MAP) estimation.
Item Type: | Dataset |
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Date Type: | Published Online |
Status: | Published |
Schools: | Computer Science & Informatics |
Publisher: | University of Bristol |
Last Modified: | 19 May 2023 02:07 |
URI: | https://orca.cardiff.ac.uk/id/eprint/145198 |
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