Multiaperture imaging.

We study the reconstruction of a high-resolution image from multiple low-resolution images by using a nonlinear iterative backprojection algorithm. We exploit diversities in the imaging channels, namely, the number of imagers, magnification, position, rotation, and fill factor, to undo the degradation caused by the optical blur, pixel blur, and additive noise. We quantify the improvements gained by these diversities in the reconstruction process and discuss the trade-off among system parameters.