Second Generation Curvelet Shrinkage Model Based Image Denoising

SECOND GENERATION CURVELET SHRINKAGE MODEL BASED IMAGE DENOISING B. Chinna Rao1 and M. Madhavi Latha2 1Department of ECE, R.K. College of Engineering, Vijaywada, A.P. India. E-mail: [email protected] 2Department of ECE, JNTU College of Engineering, Hyderabad, A.P. India. E-mail: [email protected] In this paper, a Second Generation based curvelet shrinkage is proposed for discontinuity-preserving denoising using a combination of a new second Generation curvelets with a nonlinear diffusion scheme. In order to suppress the pseudo-Gibbs and curvelet-like artifacts, the conventional shrinkage results are further processed by a projected total variation diffusion, in which only the insignificant curvelet coefficients or high frequency part of the signal are changed by use of a constrained projection. Numerical experiments from piecewise-smooth to textured images show good performances of the proposed method to recover the shape of edges and important detailed components, in comparison to some existing methods.