Open AccessMulti-resolution imaging with an optimized number and distribution of sampling points
Author(s) -
Amedeo Capozzoli,
Claudio Curcio,
Angelo Liseno
Publication year - 2014
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.22.010119
Subject(s) - sampling (signal processing) , dimension (graph theory) , optics , computer science , image resolution , synthetic aperture radar , resolution (logic) , iterative reconstruction , algorithm , radar imaging , inverse problem , inverse synthetic aperture radar , aperture (computer memory) , radar , computer vision , mathematics , artificial intelligence , physics , acoustics , telecommunications , mathematical analysis , filter (signal processing) , pure mathematics
We propose an approach of interest in Imaging and Synthetic Aperture Radar (SAR) tomography, for the optimal determination of the scanning region dimension, of the number of sampling points therein, and their spatial distribution, in the case of single frequency monostatic multi-view and multi-static single-view target reflectivity reconstruction. The method recasts the reconstruction of the target reflectivity from the field data collected on the scanning region in terms of a finite dimensional algebraic linear inverse problem. The dimension of the scanning region, the number and the positions of the sampling points are optimally determined by optimizing the singular value behavior of the matrix defining the linear operator. Single resolution, multi-resolution and dynamic multi-resolution can be afforded by the method, allowing a flexibility not available in previous approaches. The performance has been evaluated via a numerical and experimental analysis.