In this paper, we perform a statistical analysis of curvelet coefficients, distinguishing between two classes of coefficients: those that contain a significant noise-free component, which we call {"}signal of interest{"}, and those that do not. By investigating the marginal statistics, we develop a prior model for curvelet coefficients. The analysis of the joint intra- and inter-band statisticsenables us to develop an appropriate local spatial activity indicator for curvelets. Finally, based on our findings, we present a novel denoising method, inspired by a recent wavelet domain method ProbShrink. The new method outperforms its wavelet-based counterpart and produces results that are close to those of state-of-the-art denoisers.
Tessens, L, Pizurica, A, Alecu, A, Munteanu, A & Philips, W 2008, 'Context adaptive image denoising through modeling of curvelet domain statistics', Journal of Electronic Imaging, vol. 17, no. 3, 033021, pp. 1-17.
Tessens, L., Pizurica, A., Alecu, A., Munteanu, A., & Philips, W. (2008). Context adaptive image denoising through modeling of curvelet domain statistics. Journal of Electronic Imaging, 17(3), 1-17. Article 033021.
@article{964c54ba82e54c4d88488ad2bb051542,
title = "Context adaptive image denoising through modeling of curvelet domain statistics",
abstract = "In this paper, we perform a statistical analysis of curvelet coefficients, distinguishing between two classes of coefficients: those that contain a significant noise-free component, which we call {"}signal of interest{"}, and those that do not. By investigating the marginal statistics, we develop a prior model for curvelet coefficients. The analysis of the joint intra- and inter-band statisticsenables us to develop an appropriate local spatial activity indicator for curvelets. Finally, based on our findings, we present a novel denoising method, inspired by a recent wavelet domain method ProbShrink. The new method outperforms its wavelet-based counterpart and produces results that are close to those of state-of-the-art denoisers.",
keywords = "Curvelets, Image statistics, image denoising",
author = "Linda Tessens and Alexandra Pizurica and Alin Alecu and Adrian Munteanu and Wilfried Philips",
year = "2008",
month = sep,
language = "English",
volume = "17",
pages = "1--17",
journal = "Journal of Electronic Imaging",
issn = "1017-9909",
publisher = "SPIE",
number = "3",
}