Abstract
The aim of this paper is to construct a model which decomposes a 3D image into two components: the first one containing the geometrical structure of the image, the second one containing the noise. The proposed method is based on a second order variational model and an undecimated wavelet thresholding operator. The numerical implementation is described, and some experiments for denoising a 3D MRI image are successfully performed. Future prospects are finally exposed.
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Tran, MP., Péteri, R., Bergounioux, M. (2012). Denoising 3D Medical Images Using a Second Order Variational Model and Wavelet Shrinkage. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2012. Lecture Notes in Computer Science, vol 7325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31298-4_17
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DOI: https://doi.org/10.1007/978-3-642-31298-4_17
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