We present a 3D imaging system composed of a single-lens camera and a single-image depth-from-defocus (DFD) algorithm. The lens has an uncorrected chromatic aberration which induces a variation of the in-focus plane position with the wavelength. In a single snapshot of the color camera, three images with different defocus blurs are obtained, from which a depth map can be estimated. We focus here on the co-design of such a system, ie. the joint optimization of its optical and processing parameters. First, from an original calculation of the Cramer-Rao Bound we derive a theoretical model of the depth accuracy provided by such a system. Second, the performance of the system in terms of final RGB image quality is related to a "generalized depth of field". Third, these two criteria are used to design a 3D imaging system adapted to the requirements of autonomous navigation of MAV (obstacle avoidance). This system has been realized and experimentally validated and we present quantitative and qualitative depth estimation results.
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