The performance of multiview three-dimensional imaging systems depends on several factors, including the number of sensors, sensor pixel size, relative sensor configuration, imaging optics, and computational reconstruction algorithm. Therefore, it is important to compare the performance of such systems under equally constrained resources. In this Letter, we develop a unifying framework to evaluate the lateral and axial resolution of -ocular imaging systems ranging from stereo (two cameras) to multiple sensors (integral imaging) under fixed resource constraints. The proposed framework enables one to evaluate the system performance as a function of sensing parameters such as the number of cameras, the number of pixels, parallax, pixel size, lens aperture, and focal length. We carry out Monte Carlo simulations based on this framework to evaluate system performance as a function of sensing parameters. To the best of our knowledge, this is the first report on quantitative analysis of -ocular imaging systems under common resource constraints.
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