papers AI Learner
The Github is limit! Click to go to the new site.

Video from Stills: Lensless Imaging with Rolling Shutter

2019-05-30
Nick Antipa, Patrick Oare, Emrah Bostan, Ren Ng, Laura Waller

Abstract

Because image sensor chips have a finite bandwidth with which to read out pixels, recording video typically requires a trade-off between frame rate and pixel count. Compressed sensing techniques can circumvent this trade-off by assuming that the image is compressible. Here, we propose using multiplexing optics to spatially compress the scene, enabling information about the whole scene to be sampled from a row of sensor pixels, which can be read off quickly via a rolling shutter CMOS sensor. Conveniently, such multiplexing can be achieved with a simple lensless, diffuser-based imaging system. Using sparse recovery methods, we are able to recover 140 video frames at over 4,500 frames per second, all from a single captured image with a rolling shutter sensor. Our proof-of-concept system uses easily-fabricated diffusers paired with an off-the-shelf sensor. The resulting prototype enables compressive encoding of high frame rate video into a single rolling shutter exposure, and exceeds the sampling-limited performance of an equivalent global shutter system for sufficiently sparse objects.

Abstract (translated by Google)
URL

http://arxiv.org/abs/1905.13221

PDF

http://arxiv.org/pdf/1905.13221


Similar Posts

Comments