Exploiting data redundancy in computational optical imaging

We present an algorithm which exploits data redundancy
to make computational, coherent, optical imaging more computationally
efficient. This algorithm specifically addresses the computation of how
light scattered by a sample is collected and coherently detected. It is of
greatest benefit in the simulation of broadband optical systems employing
coherent detection, such as optical coherence tomography. Although also
amenable to time-harmonic data, the algorithm is designed to be embedded
within time-domain electromagnetic scattering simulators such as the
psuedo-spectral and finite-difference time domain methods. We derive the
algorithm in detail as well as criteria which ensure accurate execution of the
algorithm. We present simulations that verify the developed algorithm and
demonstrate its utility. We expect this algorithm to be important to future
developments in computational imaging.