Results 31 to 40 of about 25,862 (211)
A Noise-Robust Method with Smoothed \ell_1/\ell_2 Regularization for Sparse Moving-Source Mapping
, 2016 The method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced with a smooth \ell_1/\ell_2 regularization term. As the mean of the noise in
Mars, Jérôme I. +3 more
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A neural network approach for the blind deconvolution of turbulent flows
, 2017 We present a single-layer feedforward artificial neural network architecture trained through a supervised learning approach for the deconvolution of flow variables from their coarse grained computations such as those encountered in large eddy simulations.
Maulik, Romit, San, Omer
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Blind Ptychography via Blind Deconvolution
, 2023 arXiv admin note: text overlap with arXiv:1606.04933 by other ...
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Secure Massive IoT Using Hierarchical Fast Blind Deconvolution
, 2018 The Internet of Things and specifically the Tactile Internet give rise to significant challenges for notions of security. In this work, we introduce a novel concept for secure massive access.
Eisert, Jens +4 more
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Blind and Non-Blind Deconvolution-Based Image Deblurring Techniques for Blurred and Noisy Image
Tikrit Journal of Engineering Sciences: Image deblurring is a common issue in low-level computer vision aiming to restore a clear image from a blurred input image. Deep learning innovations have significantly advanced the solution to this issue, and numerous deblurring networks have been ...
Shayma Wail Nourildean
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Guide star based deconvolution for imaging behind turbid media
Journal of the European Optical Society-Rapid Publications, 2018 Background If structures of interest are hidden beneath turbid layers such as biological tissues, imaging becomes challenging, even impossible. However, if the point spread function of the system is known from the presence of a guide star, application of
Jale Schneider, Christof M Aegerter
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Adaptive Model for Magnetic Particle Mapping Using Magnetoelectric Sensors
Sensors, 2022 Imaging of magnetic nanoparticles (MNPs) is of great interest in the medical sciences. By using resonant magnetoelectric sensors, higher harmonic excitations of MNPs can be measured and mapped in space.
Ron-Marco Friedrich, Franz Faupel
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An Efficient Method for Non-Convex Blind Deconvolution
IEEE Access, 2019 This paper considers blind deconvolution problem that to recover unknown signals fand g from their convolution signal. Non-convex optimization approach is an efficient method to get the solution, but it is a challenge to find the exact solution for a non-
Yixian Liu
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Blind Deconvolution Using Modulated Inputs [PDF]
IEEE Transactions on Signal Processing, 2020 This paper considers the blind deconvolution of multiple modulated signals, and an arbitrary filter. Multiple inputs $\boldsymbol{s}_1, \boldsymbol{s}_2, \ldots, \boldsymbol{s}_N =: [\boldsymbol{s}_n]$ are modulated (pointwise multiplied) with random sign sequences $\boldsymbol{r}_1, \boldsymbol{r}_2, \ldots, \boldsymbol{r}_N =: [\boldsymbol{r}_n ...
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Blind deconvolution of video sequences [PDF]
2008 15th IEEE International Conference on Image Processing, 2008 We present a new blind deconvolution method for video sequence. It is derived following an inverse problem approach in a Bayesian framework. This method exploits the temporal continuity of both object and PSF Combined with edge-preserving spatial regularization, a temporal regularization constrains the blind deconvolution problem, improving its ...
Soulez, Ferréol +4 more
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