This talk will describe new microscopes that use computational imaging – the joint design of optical systems and inverse algorithms - to enable 3D imaging from a single-shot with a lensless camera consisting of only a scattering element (diffuser) placed in front of a 2D image sensor. Our reconstruction algorithms are based on large-scale nonlinear non-convex optimization with sparsity-based regularizers similar to compressed sensing.

This presentation is part of Minisymposium “MS60 - Computational and Compressive Imaging Technologies and Applications (3 parts)”
organized by: Robert Muise (Lockheed Martin) , Richard Baraniuk (Rice University) .

Authors:

Laura Waller (University of California, Berkeley)

Grace Kuo (UC Berkeley)

Nicholas Antipa (UC Berkeley)

Ren Ng (UC Berkeley)

Kyrollos Yanny (UC Berkeley)

Fanglin Liu (UC Berkeley)

Reinhard Heckel (UC Berkeley)

Keywords:

computed tomography, image reconstruction, inverse problems