Time-of-Flight Surface De-noising through Spectral Decomposition

An increasingly popular approach to the acquisition of intraoperative data is the novel Time-of-Flight (ToF) camera technique, which provides surface information with high update rates. This information can be used for intra-operative registration with pre-operative data through surface matching techniques. However, ToF data is subject to different systematic errors and noise, which must be eliminated for the purposes of matching with high-quality pre-operative data. While methods for de-noising of data concentrate on the processing of the range images, we focus directly on the surfaces. We decompose the frequency spectrum of the surface and use it for the computation of a low-pass filter, thus eliminating all the higher frequencies on the surface (noise). The low-pass filter was evaluated on in vitro data and was compared to a previously published method for ToF de-noising, which takes advantage of the fast data acquisition provided by the ToF technology. In almost all cases, the low-pass filter showed a better performance. Decomposition of the frequency spectrum of surfaces allows not only filtering and de-noising, but also the application of other valuable signal processing methods, such as enhancement or homogenization.