Optically compressed image sensing using random aperture coding

The common approach in digital imaging today is to capture as many pixels as possible and later to compress the captured image by digital means. The recently introduced theory of compressed sensing provides the mathematical foundation necessary to change the order of these operations, that is, to compress the information before it is captured. In this paper we present an optical implementation of compressed sensing. With this method, a compressed version of an object's image is captured directly. The compression is accomplished by optical means with a single exposure. One implication of this imaging approach is that the effective space-bandwidth-product of the imaging system is larger than that of conventional imaging systems. This implies, for example, that more object pixels may be reconstructed and visualized than the number of pixels of the image sensor.