Mar 29, 2024 · Compressed sensing is an optimization based formalized framework based upon sub-Nyquist sampling principle of exploiting only the sparse signal of interest. It ...

Feb 17, 2024 · developed an approach for rapid single-pixel imaging which uses a fast-spinning mask coded with cyclic sensing patterns achieving a spatial pattern modulation ...

Nov 4, 2023 · Compressive Sensing (CS) techniques reconstruct signals from measurements exploiting sparsity. If a signal exhibits sparse properties in some transform domain [ ...

Mar 1, 2024 · Progressive compressive sensing of large images with multiscale deep learning reconstruction ... This method trains a network model for compressed sensing ...

Jul 17, 2024 · We created algorithms for classifying and reconstruction images based on these measurements using classical fully connected neural networks and parameterized ...

Apr 23, 2024 · Figure 2 illustrates the workflow of CS-based 3D image reconstruction. Step ... The first two modes can perform flexible 3D imaging at video rate with ...

Mar 15, 2024 · ... image reconstruction problems such as denoising and compressive sensing. As ... We also worked with a gradient noise mode which is based on the Gaussian noise ...

Apr 23, 2024 · Compressed sensing is an algorithm that breaks through the Nyquist sampling theorem and can reconstruct the original signal with a small number of measurement ...

Sep 1, 2023 · The recovery of a high-quality image from a set of noisy measurements is fundamental in medical imaging. For instance, it is essential in compressed sensing ...

Apr 9, 2024 · Single-pixel imaging (SPI) is a potential computational imaging technique which produces image by solving an ill- posed reconstruction problem from few ...