45 citations · 109 across the 16 of their papers we have counts for
16 papers
The General sampling theorem, Compressed sensing and a method of image sampling and reconstruction with sampling rates close to the theoretical limit
L. Yaroslavsky
The article addresses the problem of image sampling with minimal possible sampling rates and reviews the recent advances in sampling theory and methods: modern formulations of the…
Compressed Sensing, ASBSR-method of image sampling and reconstruction and the problem of digital image acquisition with the lowest possible sampling rate
Leonid P. Yaroslavsky
The problem of minimization of the number of measurements needed for digital image acquisition and reconstruction with a given accuracy is addressed. Basics of the sampling theory…
How can one sample images with sampling rates close to the theoretical minimum?
Leonid Yaroslavsky
A problem is addressed of minimization of the number of measurements needed for digital image acquisition and reconstruction with a given accuracy. A sampling theory based method o…
Can compressed sensing beat the Nyquist sampling rate?
L. Yaroslavsky
Data saving capability of "Compressed sensing (sampling)" in signal discretization is disputed and found to be far below the theoretical upper bound defined by the signal sparsity.…
Is "Compressed Sensing" compressive? Can it beat the Nyquist Sampling Approach?
L. Yaroslavsky
Data compression capability of "Compressed sensing (sampling)" in signal discretization is numerically evaluated and found to be far from the theoretical upper bound defined by sig…
Compression, Restoration, Re-sampling, Compressive Sensing: Fast Transforms in Digital Imaging
Leonid Yaroslavsky
Transform image processing methods are methods that work in domains of image transforms, such as Discrete Fourier, Discrete Cosine, Wavelet and alike. They are the basic tool in im…