Upcoming Event: Tues. Sept. 10,2019

Imaging Without Lenses

Date: Tuesday, September 10, 2019

5:30pm: Networking/Light Dinner
6:30pm: Presentation
8:00pm: Adjourn


Building SC-12
3600 Juliette Lane
Santa Clara, CA 95054

(Location: Take Montague Expy. OR Great America Exit off US 101; click to see instructions)

In order for chapter officers to estimate head count for food, Registration required! Register:


Imaging Without Lenses


Nick Antipa, UCB


Traditional lens-based imaging relies on mapping each point in a scene to a single point on an imaging sensor, yielding a direct approximation to the scene. In contrast, lensless cameras rely on optics that are not one-to-one, bur rather one-to-many: each scene point is mapped to many pixels on the sensor. This permits replacing the lens with simple, compact optics such as a single phase plate, an absorption mask, or simply free space propagation. Because the resulting measurement no longer directly approximates the scene, the image must be recovered computationally. This, along with the multiplexed measurements, enable use of compressive sensing techniques to recover high dimensional signals (e.g. volumetric intensity or video) from a single snapshot measurement. This technology enables compact systems that efficiently capture high dimensional signals, holding promise for the creation of implantable in-vivo imaging devices.

Biography of Nick Antipa:

Nick Antipa earned his B.S. in Optics from UC Davis in 2008, and a M.S. in Optics from University of Rochester in 2009. He then worked at Lawrence Livermore National Lab on the National Ignition Facility project until 2014, when he left to pursue a PhD in Computational Imaging with Laura Waller and Ren Ng at UC Berkeley, where he is currently in his 6th year.