Shearlet-based total variation diffusion for denoising
IEEE Transactions on Image Processing
Fuzzy peer groups for reducing mixed Gaussian-impulse noise from color images
IEEE Transactions on Image Processing
Diffusion tensors for processing sheared and rotated rectangles
IEEE Transactions on Image Processing
Edge structure preserving image denoising using OAGSM/NC statistical model
Digital Signal Processing
Image denoising using SVM classification in nonsubsampled contourlet transform domain
Information Sciences: an International Journal
Computers & Mathematics with Applications
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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.