Adaptive anisotropic denoising: a bootstrapped procedure
(2009) 17th European Symposium on Artificail Neural Networks - Advances in Computational Intelligence and Learning (ESANN 2009) — Location: Bruges (Belgium) (22.April.2009)
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- Authors
Lee, John Aldo 
- Abstract
- Signal denoising proves to be important in many domains such as pattern recognition and image analysis. This paper investigates several refinements of adaptive local filters that rely on local mode finding. These spatial filters are anisotropic and offer the advantage of attenuating noise without smoothing salient signal features such as discontinuities or other sharp transitions. In particular, a bootstrapped procedure is developed and leads to an improvement of the denoising quality without increasing the computational complexity. Experiments with an artificial benchmark allow the quantification of the performance gain.
- Affiliations
Citations
Lee, J. A., De Decker, A., & Verleysen, M. (2009). Adaptive anisotropic denoising: a bootstrapped procedure. Proceedings of the 17th European Symposium on Artificail Neural Networks - Advances in Computational Intelligence and Learning (ESANN 2009), p. 101-106. https://hdl.handle.net/2078.5/254134