title: Fuzzy logic-based approach to wavelet denoising of 3D images produced by time-of-flight cameras.
abstract: In this paper we present a new denoising method for the depth images of a 3D imaging sensor, based on the time-of-flight principle. We propose novel ways to use luminance-like information produced by a time-of flight camera along with depth images. Firstly, we propose a wavelet-based method for estimating the noise level in depth images, using luminance information. The underlying idea is that luminance carries information about the power of the optical signal reflected from the scene and is hence related to the signal-to-noise ratio for every pixel within the depth image. In this way, we can efficiently solve the difficult problem of estimating the non-stationary noise within the depth images. Secondly, we use luminance information to better restore object boundaries masked with noise in the depth images. Information from luminance images is introduced into the estimation formula through the use of fuzzy membership functions. In particular, we take the correlation between the measured depth and luminance into account, and the fact that edges (object boundaries) present in the depth image are likely to occur in the luminance image as well. The results on real 3D images show a significant improvement over the state-of-the-art in the field.
authors.affiliation: Telecommunications and Information Processing Department, Ghent University, Sint Pietersnieuwstraat 41, 9000 Ghent, Belgium. ljj@telin.ugent.be
authors.forename: Ljubomir
authors.initials: L
authors.lastname: Jovanov
authors.forename: Aleksandra
authors.initials: A
authors.lastname: Pižurica
authors.forename: Wilfried
authors.initials: W
authors.lastname: Philips