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Compressive sensing on a CMOS separable transform image sensor

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6 Author(s)
Ryan Robucci ; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, 30332-0250, USA ; Leung Kin Chiu ; Jordan Gray ; Justin Romberg
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This paper discusses the application of a computational image sensor, capable of performing separable 2-D transforms on images in the analog domain, to compressive sensing. Instead of sensing and transmitting raw pixel data, this image sensor first projects the image onto a separable 2-D basis set. The inner products computed in these projections are computed in the analog domain using a computational focal-plane and a computational analog vector-matrix multiplier. Since this operation is performed in the analog domain, components such as the analog-to-digital converters can be taxed less when a only subset of correlations are performed. Compressed sensing theory prescribes the use of a pseudo-random, incomplete basis set, allowing for sampling at less than the Nyquist rate. This can reduce power consumption or increase frame rate.

Published in:

2008 IEEE International Conference on Acoustics, Speech and Signal Processing

Date of Conference:

March 31 2008-April 4 2008