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      A clustering based denoising technique for range images of time of flight cameras

      Schoner, H.; Moser, B.; Dorrington, Adrian A.; Payne, Andrew D.; Cree, Michael J.; Heise, B.; Bauer, F.
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      A Clustering based denoising technique.pdf
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      DOI
       10.1109/CIMCA.2008.95
      Link
       www2.computer.org
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      Schoner, H., Moser, B., Dorrington, A. A., Payne, A. D., Cree, M. J., Heise, B. & Bauer, F. (2008). A clustering based denoising technique for range images of time of flight cameras. In Masoud Mohammadian (Eds.) International Conference on Computational Intelligence for Modelling, Control and Automation; International Conference on Intelligent Agents, Web Technologies and Internet Commerce; International Conference on Innovation in Software Engineering. IEEE, Vienna, Austria; 10-12 December, 2008.(pp. 999-1004). Washington, USA: IEEE.
      Permanent Research Commons link: https://hdl.handle.net/10289/2917
      Abstract
      A relatively new technique for measuring the 3D structure of visual scenes is provided by time of flight (TOF) cameras. Reflections of modulated light waves are recorded by a parallel pixel array structure. The time series at each pixel of the resulting image stream is used to estimate travelling time and thus range information. This measuring technique results in pixel dependent noise levels with variances changing over several orders of magnitude dependent on the illumination and material parameters. This makes application of traditional (global) denoising techniques suboptimal. Using free aditional information from the camera and a clustering procedure we can get information about which pixels belong to the same object, and what their noise level is, which allows for locally adapted smoothing. To illustrate the success of this method, we compare it with raw camera output and a traditional method for edge preserving smoothing, anisotropic diffusion [10, 12]. We show that this mathematical technique works without individual adaptations on two camera systems with highly different noise characteristics.
      Date
      2008
      Type
      Conference Contribution
      Publisher
      IEEE
      Rights
      ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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