Hardware Friendly Spline Sketched Lidar
Michael Sheehan (University of Edinburgh); Julián Tachella (CNRS & ENS de Lyon); Mike Davies (University of Edinburgh)
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Photon counting lidar has become an invaluable tool for 3D depth imaging due to the fine-precision it can achieve over long ranges. However, high frame rate, high resolution lidar devices produce an enormous amount of time-of-flight (ToF) data which can hinder the deployment of real-time systems. In this paper, an efficient photon acquisition approach is proposed that exploits the simplicity of piecewise polynomial splines to form a hardware-friendly compressed statistic, or spline sketch, of the ToF data. We show that a piecewise linear or quadratic spline sketch, requires minimal on-chip arithmetic computation per photon detection and can reconstruct real-world depth images using a simple closed form solution. Further, by building range-walk correction into the proposed estimation algorithms, it is demonstrated that the spline sketches can be made robust to photon pile-up effects.