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Feasibility study for super-resolution 3D integral imaging using time-multiplexed compressive coding.

We propose a novel super-resolution 3D II method using a time-multiplexed coding mask for improving the resolution of 3D imaging based on compressive sensing (CS) theory. Instead of sensing raw pixel data, the recording device measures the compressive samples of the observed 3D scene through a coding mask placed in the aerial pickup plane in a 3D II system. With the aid of CS framework, we design an optimum coding mask pattern and use the time-multiplexed scheme to achieve a sequence of low-resolution elemental images (EIs), which contain the subpixel details of the observed 3D scene. The super-resolution EIs array is further recovered by an optimization algorithm. Both computational reconstruction and optical experimental results show the validity of the proposed method.