Evaluation and Compensation of the Effect of Dirt on Time-of-Flight 3D Imaging Systems

In the past few years, 3D imaging technology has received a lot of attention. Time-of-Flight (ToF) cameras based on the indirect ToF principle calculate depth information by measuring the phase shift between the emitted periodic signal and the reflected signal. When the illumination from the modulated light source reaches the same pixel through multiple paths, multipath interference will occur. Acquisitions at multiple modulation frequencies are then required to separate the interfering paths. Parametric spectral estimation methods, such as Prony’s method and its robust variants, have shown success in resolving multiple paths from multi-frequency measurements. With the widespread usage of ToF cameras in various fields, the operating environment of the camera should be taken into account in order to obtain accurate 3D images. In this work, we aim to study the effect of dirt on 3D imaging systems quantitatively. To this end, ten sheets with different transmittances, between 50% and 100% are used. To the best of our knowledge, for the first time we provide standardized methods for evaluating the effect of dirt on protective covers in the depth estimation of “flash lidar”. The accuracy of depth measurements obtained by multi-frequency multipath recovery in the absence of dust is up to 99%. However, when the light transmittance of the protective cover is less than 90%, the measurement result is already unreliable. The experiments have shown that the depth measurements obtained using the multi-frequency estimation method are more accurate in the presence of dust than the single-frequency estimation method.