Image processing for three-dimensional scans generated by time-of-flight range cameras

Abstract

Time-of-flight (TOF) full-field range cameras use a correlative imaging technique to generate three-dimensional measurements of the environment. Though reliable and cheap they have the disadvantage of high measurement noise and errors that limit the practical use of these cameras in industrial applications. We show how some of these limitations can be overcome with standard image processing techniques specially adapted to TOF camera data. Additional information in the multimodal images recorded in this setting, and not available in standard image processing settings, can be used to improve reduction of measurement noise. Three extensions of standard techniques, wavelet thresholding, adaptive smoothing on a clustering based image segmentation, and an extended anisotropic diffusion filtering, make use of this information and are compared on synthetic data and on data acquired from two different off-the-shelf TOF cameras. Of these methods, the adapted anisotropic diffusion technique gives best results, and is implementable to perform in real time using current graphics processing unit (GPU) hardware. Like traditional anisotropic diffusion, it requires some parameter adaptation to the scene characteristics, but allows for low visualization delay and improved visualization of moving objects by avoiding long averaging periods when compared to traditional TOF image denoising.

Denoising 3D images from time-of-flight cameras using extended anisotropic diffusion

“…Measurements of intensity and range made using this acquisition scheme are affected by certain kinds of noise. 1 In particular, very high levels of noise occur in range-image regions with low levels of reflected light 2 (e.g., dark image patches) because less data is available for estimating range. By the same token, regions of high reflection exhibit noise levels orders of magnitude lower.…”

“…We have described three alternatives that extend standard denoising approaches to make use of the additional information available in TOF imaging by virtue of two linked (intensity and range) images. 1,3 The intensity image gives information about noise levels in range-image regions that can be used for local adaptation of the denoising parameters. The alternative methods are these: We adapt the threshold in wavelet thresholding to local noise levels.…”