Approach for Pseudo-random bit-stream multi-depth imaging

Pseudo-random spread spectrum photon counting is a well-established technique for three-dimensional imaging. We present a fast imaging technique that is able to accurately recover multi-depth at individual pixels based on pseudo-random spread spectrum photon counting systems. Firstly, the accelerated Richardson–Lucy iterative deconvolution algorithm is introduced. After the post-processing stage, the peaks are well-separated and the depth values are calculated. For multi-depth estimation in the presence of moderate background light, we experimentally demonstrate that our imaging technique outperforms the conventional RL method. We have successfully improved the range resolution from 15 to 6 cm, thus breaking the full width at half-maximum resolution limit. The separation root mean square error has been reduced to 2.6 cm by the proposed method for the surface-to-surface separation of 6 cm. The depth image of the elephant placed 6 cm behind the partially-reflective object has been accurately reconstructed.