Sparsity-Driven Reconstruction Technique for Microwave/Millimeter-Wave Computational Imaging
نویسندگان
چکیده
منابع مشابه
Sparsity driven ultrasound imaging.
An image formation framework for ultrasound imaging from synthetic transducer arrays based on sparsity-driven regularization functionals using single-frequency Fourier domain data is proposed. The framework involves the use of a physics-based forward model of the ultrasound observation process, the formulation of image formation as the solution of an associated optimization problem, and the sol...
متن کاملSparsity-Driven Synthetic Aperture Radar Imaging
This paper presents a survey of recent research on sparsity-driven synthetic aperture radar (SAR) imaging. In particular, it reviews (i) analysis and synthesis-based sparse signal representation formulations for SAR image formation together with the associated imaging results; (ii) sparsity-based methods for wide-angle SAR imaging and anisotropy characterization; (iii) sparsity-based methods fo...
متن کاملSparsity-Based Data Reconstruction Models for Biomedical Imaging
We propose new regularization models to solve inverse problems encountered in biomedical imaging applications. In formulating mathematical schemes, we base our approach on the sparse signal processing principles that have emerged as a central paradigm in the field. We adopt a variational perspective and specify the proposed sparsity-promoting data reconstruction models as energy minimization pr...
متن کاملReconstruction , autofocusing , moving targets , and compressed sensing ] Sparsity - Driven Synthetic Aperture Radar Imaging
Date of publication: 13 June 2014 T his article presents a survey of recent research on sparsity-driven synthetic aperture radar (SAR) imaging. In particular, it reviews 1) the analysis and synthesis-based sparse signal representation formulations for SAR image formation together with the associated imaging results, 2) sparsity-based methods for wide-angle SAR imaging and anisotropy characteriz...
متن کاملSampling and Reconstruction driven by Sparsity Models: Theory and Applications
It has been shown recently that it is possible to sample classes of non-bandlimited signals which we call signals with Finite Rate of Innovation (FRI). Perfect reconstruction is possible based on a set of suitable measurements and this provides a sharp result on the sampling and reconstruction of sparse continuous-time signals. In this paper, we first review the basic theory and results on samp...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Sensors
سال: 2018
ISSN: 1424-8220
DOI: 10.3390/s18051536