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19 May 2005 Regularization based super resolution imaging using FFT:s
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Abstract
This paper address the problem of super resolution imaging, using regularized amplitude estimation. Using a Bayesian problem formulation the regularization is applied through a prior distribution of the amplitudes. We investigate both a "super Gaussian" and a Student-t prior distribution. We derive maximum a posteriori (MAP) estimators for the amplitudes, based on the "Space-Alternating Generalized Expectation-Maximization" (SAGE) method, that only uses FFT:s in each iteration. The behavior of the algorithms for different choices of regularization parameters are illustrated through simple one dimensional examples, and SAR imaging is illustrated through an example using MSTAR data.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Roland Jonsson "Regularization based super resolution imaging using FFT:s", Proc. SPIE 5808, Algorithms for Synthetic Aperture Radar Imagery XII, (19 May 2005); https://doi.org/10.1117/12.604347
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