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3D Imager Design through Multiple Aperture Optimization

3D imagers exhibit a tradeoff between device size and accuracy. We design compact and accurate 3D imagers by optimizing subsystem parameters using a multiple-aperture image simulator and an accuracy estimator operating on distorted views. In this paradigm, each subsystem records different information about the scene. The difference could be in viewing angle, optical transfer function, polarization, or spectral properties of the subsystems. We find a high-accuracy multiple-aperture configuration that minimizes a quality metric based on 3D position estimation uncertainties. We estimate such 3D uncertainties by estimating object positions from simulated multiple-aperture responses using a closed-form solution for position
estimation and a Monte Carlo simulation for uncertainty estimation, after accounting for physical imaging effects such as diffraction, aberrations, distortion, quantization, and noise. [See COSI 2011]