CS-ToF Sensing by means of Greedy Bi-lateral Fusion and Near-to-optimal Low-density Codes

In this work, we propose a sensing scheme for the reconstruction of a highly sparse 3D view by a Pulse-Based Time-of-Flight (PB-ToF) camera aiming at achieving high angular resolution at interactive rates. The construction of the sensing matrices is focused on the optimization of the coherence and the preservation of the low density which characterize Low-Density Parity-Check (LDPC) codes. We investigate the possibility of shifting the custom sequences generated at the pixel level by selecting the shifts which maximize the minimum distance between adjacent columns, as well as the use of the information from the two complementary integration channels or taps the ToF sensor consists of. The signal reconstruction algorithm, coinedgreedy bi-lateral fusion, firstly determines a preliminary target probability distribution, and then re-weights it by exploiting the local correlations within the pixel array by applying a bi-lateral filtering which accounts for the affinities in spatial and intensity domains. The algorithm improves the accuracy of our camera under presence of strong noise and still preserves the speed and simplicity associated to classical greedy algorithms