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Normally Distributed Perturbations Method for Extraction of Less Significant Peaks Resolution in Radar Image Focusing Applications

Mahdi Jalali

Attempting to extend approaches to signal estimation in a wavelet framework, which have generally relied on the assumption of normally distributed perturbations, we propose a novel non-linear altering technique, as a pre-processing step for the shapes obtained from an ISAR imaging system. The key idea is to project a noisy shape onto a wavelet domain and to suppress wavelet coefficients by a mask derived from curvature extreme in its scale space representation. To identify a shape independently of its registration information. In particular, we study the generalized matching by estimating mean shapes in two dimensions. Simulation results show that matching by way of a mean shape is more robust than matching target shapes directly