TY - GEN
T1 - CS-MUVI
T2 - 2012 IEEE International Conference on Computational Photography, ICCP 2012
AU - Sankaranarayanan, Aswin C.
AU - Studer, Christoph
AU - Baraniuk, Richard G.
PY - 2012
Y1 - 2012
N2 - Compressive sensing (CS)-based spatial-multiplexing cameras (SMCs) sample a scene through a series of coded projections using a spatial light modulator and a few optical sensor elements. SMC architectures are particularly useful when imaging at wavelengths for which full-frame sensors are too cumbersome or expensive. While existing recovery algorithms for SMCs perform well for static images, they typically fail for time-varying scenes (videos). In this paper, we propose a novel CS multi-scale video (CS-MUVI) sensing and recovery framework for SMCs. Our framework features a co-designed video CS sensing matrix and recovery algorithm that provide an efficiently computable low-resolution video preview. We estimate the scene's optical flow from the video preview and feed it into a convex-optimization algorithm to recover the high-resolution video. We demonstrate the performance and capabilities of the CS-MUVI framework for different scenes.
AB - Compressive sensing (CS)-based spatial-multiplexing cameras (SMCs) sample a scene through a series of coded projections using a spatial light modulator and a few optical sensor elements. SMC architectures are particularly useful when imaging at wavelengths for which full-frame sensors are too cumbersome or expensive. While existing recovery algorithms for SMCs perform well for static images, they typically fail for time-varying scenes (videos). In this paper, we propose a novel CS multi-scale video (CS-MUVI) sensing and recovery framework for SMCs. Our framework features a co-designed video CS sensing matrix and recovery algorithm that provide an efficiently computable low-resolution video preview. We estimate the scene's optical flow from the video preview and feed it into a convex-optimization algorithm to recover the high-resolution video. We demonstrate the performance and capabilities of the CS-MUVI framework for different scenes.
UR - http://www.scopus.com/inward/record.url?scp=84863660767&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863660767&partnerID=8YFLogxK
U2 - 10.1109/ICCPhot.2012.6215212
DO - 10.1109/ICCPhot.2012.6215212
M3 - Conference contribution
AN - SCOPUS:84863660767
SN - 9781467316613
T3 - 2012 IEEE International Conference on Computational Photography, ICCP 2012
BT - 2012 IEEE International Conference on Computational Photography, ICCP 2012
Y2 - 28 April 2012 through 29 April 2012
ER -