Image denoising using nonsubsampled contourlet transform
一种无抽样Contourlet变换的图像去噪方法

To remove noise from image a method based on Contourlet Transform was proposed. The construction of Contourlet Transform is based on a nonsubsampled pyramid structure and nonsubsampled Directional Filter Banks. The threshold for coefficients shrinkage was tracked across scales and a library for scale-dependent threshold was built by performing Contourlet Transform on simulated Gaussian noise samples. Images that are corrupted with additive Gaussian noise were de-noised by coefficients shrinkage where threshold was looked up directly in library by estimating standard deviation of noise. The experimental results show that the proposed approach performs effectively in terms of both vision and the PSNR values.