Parametric surface denoising

Ioannis A. Kakadiaris, Ioannis Konstantinidis, Manos Papadakis, Wei Ding, Lixin Shen

Research output: Contribution to journalConference Articlepeer-review


Three dimensional (3D) surfaces can be sampled parametrically in the form of range image data. Smoothing/denoising of such raw data is usually accomplished by adapting techniques developed for intensity image processing, since both range and intensity images comprise parametrically sampled geometry and appearance measurements, respectively. We present a transform-based algorithm for surface denoising, motivated by our previous work on intensity image denoising, which utilizes a non-separable Parseval frame and an ensemble thresholding scheme. The frame is constructed from separable (tensor) products of a piecewise linear spline tight frame and incorporates the weighted average operator and the Sobel operators in directions that are integer multiples of 45°. We compare the performance of this algorithm with other transform-based methods from the recent literature. Our results indicate that such transform methods are suited to the task of smoothing range images.

Original languageEnglish (US)
Article number59141K
Pages (from-to)1-11
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2005
Externally publishedYes
EventWavelets XI - San Diego, CA, United States
Duration: Jul 31 2005Aug 3 2005


  • Surface denoising
  • Tight frame
  • Wavelets

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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