Coded aperture imaging with multiple measurements

Abstract

In coded aperture imaging, only aperture arrays consisting of (0, 1) elements are physically realizable. If multiple coded images are obtained with different aperture masks and the resulting detector images are suitably combined, a larger variety of aperture arrays, such as multilevel, complex-valued, vector-valued, or complementary arrays becomes applicable. We present a general theory of coded aperture imaging with multiple measurements. An image reconstruction scheme from the coded images is described that results in a maximum signal-to-noise ratio. Also, the design of sets of aperture arrays is addressed and explicitly solved for several important cases. It is shown how known classes of correlation arrays can be beneficially applied to coded aperture imaging.