Results 11 to 20 of about 1,596,426 (191)
Sparse Reconstruction for Near-Field MIMO Radar Imaging using Fast Multipole Method
IEEE Access, 2021 Radar imaging using multiple input multiple output systems are becoming popular recently. These applications typically contain a sparse scene and the imaging system is challenged by the requirement of high quality real-time image reconstruction from ...
E. A. Miran, F. Oktem, S. Koc
semanticscholar +3 more sources
Photoacoustics, 2023 As a non-invasive hybrid biomedical imaging technology, photoacoustic tomography combines high contrast of optical imaging and high penetration of acoustic imaging.
Xianlin Song +7 more
semanticscholar +3 more sources
Fluids, 2019 Sparse linear estimation of fluid flows using data-driven proper orthogonal decomposition (POD) basis is systematically explored in this work. Fluid flows are manifestations of nonlinear multiscale partial differential equations (PDE) dynamical systems ...
Balaji Jayaraman +2 more
semanticscholar +3 more sources
Sparse Reconstruction of Sound Field Using Bayesian Compressive Sensing and Equivalent Source Method. [PDF]
Sensors (Basel), 2023 To solve the problem of sound field reconstruction with fewer measurement points, a sound field reconstruction method based on Bayesian compressive sensing is proposed.
Xiao Y, Yuan L, Wang J, Hu W, Sun R.
europepmc +2 more sources
Gradient Projection with Approximate L₀ Norm Minimization for Sparse Reconstruction in Compressed Sensing. [PDF]
Sensors (Basel), 2018 In the reconstruction of sparse signals in compressed sensing, the reconstruction algorithm is required to reconstruct the sparsest form of signal. In order to minimize the objective function, minimal norm algorithm and greedy pursuit algorithm are most ...
Wei Z +5 more
europepmc +2 more sources
Near-Field 3D Sparse SAR Direct Imaging with Irregular Samples
Remote Sensing, 2022 Sparse imaging is widely used in synthetic aperture radar (SAR) imaging. Compared with the traditional matched filtering (MF) methods, sparse SAR imaging can directly image the scattered points of a target and effectively reduce the sidelobes and clutter
Shiqi Xing +5 more
doaj +1 more source
Dynamic Orthogonal Matching Pursuit for Sparse Data Reconstruction
IEEE Open Journal of Signal Processing, 2023 The orthogonal matching pursuit (OMP) is one of the mainstream algorithms for sparse data reconstruction or approximation. It acts as a driving force for the development of several other greedy methods for sparse data reconstruction, and it also plays a ...
Yun-Bin Zhao, Zhi-Quan Luo
doaj +1 more source
Multi-Objective Sparse Reconstruction With Transfer Learning and Localized Regularization
IEEE Access, 2020 Multi-objective sparse reconstruction methods have shown strong potential in sparse reconstruction. However, most methods are computationally expensive due to the requirement of excessive functional evaluations.
Bai Yan +3 more
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Coarse-to-Fine Sparse Transformer for Hyperspectral Image Reconstruction [PDF]
European Conference on Computer Vision, 2022 Many algorithms have been developed to solve the inverse problem of coded aperture snapshot spectral imaging (CASSI), i.e., recovering the 3D hyperspectral images (HSIs) from a 2D compressive measurement.
Jing Lin +7 more
semanticscholar +1 more source
Sparse Reconstruction for Micro Defect Detection in Acoustic Micro Imaging. [PDF]
Sensors (Basel), 2016 Acoustic micro imaging has been proven to be sufficiently sensitive for micro defect detection. In this study, we propose a sparse reconstruction method for acoustic micro imaging.
Zhang Y +6 more
europepmc +2 more sources