ICIP 2006, Atlanta, GA

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Paper Detail

Session:Signal/Image Reconstruction from Sparse Measurements
Time:Tuesday, October 10, 11:20 - 11:40
Presentation: Special Session Lecture
Topic: Special Sessions: Signal/image reconstruction from sparse measurements
Authors: Michael Wakin; Rice University 
 Jason Laska; Rice University 
 Marco Duarte; Rice University 
 Dror Baron; Rice University 
 Shriram Sarvotham; Rice University 
 Dharmpal Takhar; Rice University 
 Kevin Kelly; Rice University 
 Richard Baraniuk; Rice University 
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.