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An Architecture for Compressive Imaging

Submitted by Jaska on Sat, 08/05/2006 - 7:34am.

Authors:

Michael B. Wakin; Jason N. Laska; Marco F. Duarte; Dror Baron; Shriram Sarvotham; Dharmpal Takhar; Kevin F. Kelly; Richard G. Baraniuk

Source:

Proc. International Conference on Image Processing (ICIP), Atlanta, GA (2006)

URL:

http://www.ece.rice.edu/~jnl5066/papers/CSCam-ICIP06.pdf

Keywords:

Data Acquisition; Data Compression; Image Coding; Image Sensors; Video Coding

Abstract:

Compressive Sensing is an emerging field based on the revelation that a small group of non-adaptive linear projections of a compressible signal contains enough information for reconstruction and processing. In this paper, we propose algorithms and hardware to support a new theory of Compressive Imaging. Our approach is based on a new digital image/video camera that directly acquires random projections of the signal without first collecting the pixels/voxels. Our camera architecture employs a digital micromirror array to perform optical calculations of linear projections of an image onto pseudorandom binary patterns. Its hallmarks include the ability to obtain an image with a single detection element while measuring the image/video fewer times than the number of pixels — this can significantly reduce the computation required for video acquisition/encoding. Because our system relies on a single photon detector, it can also be adapted to image at wavelengths that are currently impossible with conventional CCD and CMOS imagers. We are currently testing a prototype design for the camera and include experimental results.

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