Nonlinear Regularized Reaction-Diffusion Filters for Denoising of Images With Textures

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. Key words. reaction-diffusion, second-generation curvelets, wave atoms, digital TV, regularization, denoising

• Type: Journal
• Year: 2008
• Where: TIP
• Authors: Gerlind Plonka, Jianwei Ma
• Keywords: Denoising, Directional Wavelet Frames, TIP 2008, Wave Atom Shrinkage