Sensor resolution of 3D time-of-flight (ToF) outdoor-capable cameras is strongly limited because of its large pixel dimensions. Computational imaging permits enhancement of the optical system’s resolving power without changing physical sensor properties. Super-resolution (SR) algorithms superimpose several sub-pixel-shifted low-resolution (LR) images to overcome the system’s limited spatial sampling rate. In this paper, we propose a novel opto-mechanical system to implement sub-pixel shifts by moving an optical lens. This method is more flexible in terms of implementing SR techniques than current sensor-shift approaches. In addition, we describe a SR observation model that has been optimized for the use of LR 3D ToF cameras. A state-of-the-art iteratively reweighted minimization algorithm executes the SR process. It is proven that our method achieves nearly the same resolution increase as if the pixel area would be halved physically. Resolution enhancement is measured objectively for amplitude images of a static object scene.

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