University of California, Riverside

Department of Electrical and Computer Engineering

A Talk on "Ultra-miniature Lensless Computational Imagers and Sensors" Presented by Dr. David Stork, Rambus Labs

A Talk on "Ultra-miniature Lensless Computational Imagers and Sensors" Presented....

A Talk on "Ultra-miniature Lensless Computational Imagers and Sensors" Presented by Dr. David Stork, Rambus Labs

April 7, 2014 - 11:10 am
Winston Chung Hall, 205/206




We describe a new class of computational optical sensors and imagers that do not rely on traditional refractive or reflective focusing but instead on special diffractive optical elements integrated with CMOS photodiode arrays.  The diffractive elements have provably optimal optical properties essential for imaging, and act as a visual chirp and preserve full Fourier image information on the photodiode arrays.  Images are not captured, as in traditional imaging systems, but rather computed from raw photodiode signals.  Because such imagers forgo the use of lenses, they can be made unprecedentedly small—as small as the cross-section of a human hair.  Such imagers have extended depth of field, from roughly 1mm to infinity, and should find use in numerous applications, from endoscopy to infra-red and surveillance imaging and more.  Furthermore, the gratings and signal processing can be tailored to specific applications from visual motion estimation to barcode reading and others.



David G. Stork is Distinguished Research Scientist and Research Director of the Computational Sensing and Imaging Group at Rambus Labs.  A graduate in physics from MIT and the University of Maryland, Dr. Stork has published eight books/proceedings volumes, including Pattern classification (2nd ed.) and Seeing the Light:  Optics in nature, photography, color, vision and holography and has held faculty appointments in eight disciplines variously at Wellesley and Swarthmore Colleges and Clark, Boston and Stanford Universities.  He holds 43 issued patents and is Fellow of both the International Association for Pattern Recognition and of SPIE.




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Electrical and Computer Engineering
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University of California, Riverside
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