Denoising Time-Of-Flight Data with Adaptive Total Variation

For denoising depth maps from time-of-flight (ToF) cameras we propose an adaptive total variation based approach of first and second order. This approach allows us to take into account the geometric properties of the depth data, such as edges and slopes. To steer adaptivity we utilize a special kind of structure tensor based on both the amplitude and phase of the recorded ToF signal. A comparison to state-of-the-art denoising methods shows the advantages of our approach.