The goal of spectral imaging is to capture the spectral signature of a target. Traditional
scanning method for spectral imaging suffers from large system volume and low image …

Capturing high-dimensional (HD) data is a long-term challenge in signal processing and
related fields. Snapshot compressive imaging (SCI) uses a 2D detector to capture HD (≥ …

Deep learning is becoming an increasingly important tool for image reconstruction in
fluorescence microscopy. We review state-of-the-art applications such as image restoration …

Computational imaging through scatter generally is accomplished by first characterizing the
scattering medium so that its forward operator is obtained and then imposing additional …

Lensless imaging provides opportunities to design imaging systems free from the constraints
imposed by traditional camera architectures. Due to advances in imaging hardware …

The simple and compact optics of lensless microscopes and the associated computational
algorithms allow for large fields of view and the refocusing of the captured images. However …

Miniature fluorescence microscopes are a standard tool in systems biology. However,
widefield miniature microscopes capture only 2D information, and modifications that enable …

In recent years, there has been a significant transformation in the field of incoherent imaging
with new possibilities of compressing three-dimensional (3D) information into a two …

Multiplexing multiple orbital angular momentum (OAM) channels enables high-capacity
optical communication. However, optical scattering from ambient microparticles in the …

This article covers recent advances in the fusion of metasurface antenna design and
computational imaging (CI) concepts for the realization of imaging systems that are planar …