Patch-Based Bilateral Filter and Local M-Smoother for Image Denoising
(2009) 17th European Symposium on Artifician Neural Networks - Advances in Computational Intellignece and Learning (ESANN′09) — Location: Bruges (Belgium) (22.April.2009)
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- Abstract
- In the field of image analysis, denoising is an important preprocessing task. The design of an efficient, robust, and computationally effective edge preserving denoising algorithm is a widely studied, and yet unsolved problem. One of the most efficient edge-preserving denoising algorithms is the bilateral filter, which is an intuitive generalization of the local M-smoother. In this paper, we propose to modify both the bilateral filter and the local M-smoother to use patches of the image instead of single pixels in the denoising process. With this modification, the filtering effect becomes more sensitive to the different areas of the image and the filtering results improve. The denoising quality of these patch-based filters is evaluated on test images and compared to the classical bilateral filtering and local M-smoother.
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Citations
De Decker, A., Lee, J., & Verleysen, M. (2009). Patch-Based Bilateral Filter and Local M-Smoother for Image Denoising. Proceedings of the 17th European Symposium on Artifician Neural Networks - Advances in Computational Intellignece and Learning (ESANN 2009), p. 95-100. https://hdl.handle.net/2078.5/253928