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• W2119288742 startingPage "1283" @default.
• W2119288742 abstract "Denoising is always a challenging problem in natural imaging and geophysical data processing. In this paper, we consider the denoising of texture images using a nonlinear reaction-diffusion equation and directional wavelet frames. In our model, a curvelet shrinkage is used for regularization of the diffusion process to preserve important features in the diffusion smoothing and a wave atom shrinkage is used as the reaction in order to preserve and enhance interesting oriented textures. We derive a digital reaction-diffusion filter that lives on graphs and show convergence of the corresponding iteration process. Experimental results and comparisons show very good performance of the proposed model for texture-preserving denoising." @default.
• W2119288742 created "2016-06-24" @default.
• W2119288742 creator A5059739223 @default.
• W2119288742 creator A5078652354 @default.
• W2119288742 date "2008-08-01" @default.
• W2119288742 modified "2023-09-27" @default.
• W2119288742 title "Nonlinear Regularized Reaction-Diffusion Filters for Denoising of Images With Textures" @default.
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• W2119288742 doi "https://doi.org/10.1109/tip.2008.925305" @default.
• W2119288742 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/18632339" @default.
• W2119288742 hasPublicationYear "2008" @default.
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