Title: Fast Depth Imaging Denoising with the Temporal Correlation of Photons,
Abstract: This paper proposes a novel method to filter out the false alarm of LiDAR
system by using the temporal correlation of target reflected photons. Because
of the inevitable noise, which is due to background light and dark counts of
the detector, the depth imaging of LiDAR system exists a large estimation
error. Our method combines the Poisson statistical model with the different
distribution feature of signal and noise in the time axis. Due to selecting a
proper threshold, our method can effectively filter out the false alarm of
system and use the ToFs of detected signal photons to rebuild the depth image
of the scene. The experimental results reveal that by our method it can fast
distinguish the distance between two close objects, which is confused due to
the high background noise, and acquire the accurate depth image of the scene.
Our method need not increase the complexity of the system and is useful in
power-limited depth imaging.