3 Michael Wakin Jason Laska Marco Duarte Dror Baron Shriram Sarvotham Dharmpal Takhar Kevin Kelly Richard Baraniuk 2006 Proc. Picture Coding Symposium (PCS) Beijing, China camera, compressive sensing, imaging, incoherent projections, linear programming, random matrices, sparsity, video Compressive Sensing is an emerging field based on the revelation that a small group of nonadaptive 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 light field 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/voxels; this can significantly reduce the computation required for video acquisition/encoding. Since 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. http://www.ece.rice.edu/~jnl5066/papers/pcs-camera.pdf