The emerging field of compressed sensing has potentially powerful implications for the
design of optical imaging devices. In particular, compressed sensing theory suggests that …

As a greedy algorithm to recover sparse signals from compressed measurements,
orthogonal matching pursuit (OMP) algorithm has received much attention in recent years. In …

The breadth, complexity, and volume of data generated by materials characterization using
various forms of microscopy has expanded significantly. Combined with increases in …

Hyperspectral imaging is a powerful technology for remotely inferring the material properties
of the objects in a scene of interest. Hyperspectral images consist of spatial maps of light …

The computational ghost imaging with a phase spatial light modulator (SLM) for wave field
coding is considered. A transmission-mask amplitude object is reconstructed from multiple …

We present a mathematical connection between channel coding and compressed sensing.
In particular, we link, on the one hand, channel coding linear programming decoding (CC …

Non-line-of-sight (NLOS) imaging techniques have the ability to look around corners, which
is of growing interest for diverse applications. We explore compressed sensing in active …

In the theory of compressed sensing (CS), the sparsity\| x\| _0 of the unknown signal x∈\R^
p is commonly assumed to be a known parameter. However, it is typically unknown in …

This paper proposes and develops inexact proximal methods for finding stationary points of
the sum of a smooth function and a nonsmooth weakly convex one, where an error is …

We present a theory for Euclidean dimensionality reduction with subgaussian matrices
which unifies several restricted isometry property and Johnson–Lindenstrauss-type results …