183 citations · 684 across the 16 of their papers we have counts for
5 papers · 1 filter
Detecting clear-air turbulence via beam broadening in a Rayleigh-scattering lidar system
Christopher Miller, Daniel Lum, Brandon Rodenburg +4
The volume of clear-air turbulence (CAT) in the atmosphere at flight cruising altitudes is increasing rapidly, posing a growing problem for civil aviation and resulting in reduced…
Compressively sampling the optical transmission matrix of a multimode fibre
Shuhui Li, Charles Saunders, Daniel J. Lum +4
Measurement of the optical transmission matrix (TM) of an opaque material is an advanced form of space-variant aberration correction. Beyond imaging, TM-based methods are emerging…
Compressive Direct Imaging of a Billion-Dimensional Optical Phase-Space
Samuel H. Knarr, Daniel J. Lum, James Schneeloch +1
Optical phase-spaces represent fields of any spatial coherence, and are typically measured through phase-retrieval methods involving a computational inversion, interference, or a r…
Compressive Wavefront Sensing with Weak Values
Gregory A. Howland, Daniel J. Lum, John C. Howell
We demonstrate a wavefront sensor based on the compressive sensing, single-pixel camera. Using a high-resolution spatial light modulator (SLM) as a variable waveplate, we weakly co…
Photon counting compressive depth mapping
Gregory A. Howland, Daniel J. Lum, Matthew R. Ware +1
We demonstrate a compressed sensing, photon counting lidar system based on the single-pixel camera. Our technique recovers both depth and intensity maps from a single under-sampled…