@inproceedings{10845ff4bfc2457a87974000d5592eb3,
title = "An architecture for compressive imaging",
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.",
keywords = "Data acquisition, Data compression, Image coding, Image sensors, Video coding",
author = "Wakin, {Michael B.} and Laska, {Jason N.} and Duarte, {Marco F.} and Dror Baron and Shriram Sarvotham and Dharmpal Takhar and Kelly, {Kevin F.} and Baraniuk, {Richard G.}",
year = "2006",
doi = "10.1109/ICIP.2006.312577",
language = "English (US)",
isbn = "1424404819",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "1273--1276",
booktitle = "2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings",
note = "2006 IEEE International Conference on Image Processing, ICIP 2006 ; Conference date: 08-10-2006 Through 11-10-2006",
}