Noise removal approach using Curvelet transform
Wei Jin · Guangdian gongcheng · 2005
Edges in image feature one kind of linear singularity.The aim of Multiscale Geometric Analysis(MGA) which includes Curvelet transform and Ridgelet Transform is to find a kind of optimal representation of such type of image in the sense of nonlinear approximation.Based on Curvelet transform,one image denoising approach is proposed in the paper.Due to the inherent relativity between Curvelet coefficients,this method adopts Curvelet coefficients adaptively with WindowShrink scheme via window/neighborhood processing.Experiments show that this method not only keeps the edge of image but also yields de-noised images with higher PSNR value(PSNR = 29.93 with noise variance σ=25) and better visual quality.