Denoising of continuous-wave time-of-flight depth images using confidence measures

Abstract Time-of-flight range sensors with on-chip continuous-wave correlation of radio frequency modulated signals are increasingly popular. They simultaneously deliver depth maps and intensity images with noise and systematic errors that are unique for this particular kind of data. Based on recent theoretical findings on the dominating noise processes we propose specific variants of normalized convolution and median filtering, both adaptive and non-adaptive, to the denoising of the range images. We examine the proposed filters on real-world depth maps with varying reflectivity, structure, over-exposure, and illumination. The best results are obtained by adaptive filters that locally adjust the level of smoothing using the estimated modulation amplitude as a measure of confidence.