基于组合双密度复小波变换和双变量模型的图像去噪算法

his paper proposes a new image denoising method based on the permuted Double-Density Complex Wavelet Transform and the Bivariate model. The proposed algorithm get the decomposition coefficients useing the Double-Density Complex Wavelet Transform first, and permute the coefficients which can stress the edge informations of images. The Bivariate model under the framework of Bayesian MAP estimation theory can exploit the intra-scale and inter-scale correlations of coefficients, and it improved the effect of image denoising. Compared with some current outstanding denoising methods, the simulation results and analysis show that the proposed algorithm removes Gibbs-like phenomenon, and obviously outperformes in both Peak Signal-to-Noise Ratio(PSNR) and visual quality,and effectively preserves detail and texture information of original images.