Adaptive bilateral filter and Bayesian threshold based image denoising

In this paper a hybrid denoising algorithm which combines adaptive bilateral Filter and Bayesian thresholding for digital images corrupted by Gaussian noise is proposed. The wavelet filter bank is used to decompose the image into approximation sub band and detail sub band. The adaptive bilateral filter is applied to approximation sub band and Bayesian thresholding is applied to detail sub band. The proposed algorithm is tested on gaussian noise corrupted images. The observation of parameters like visual quality results and quantitative performance in terms of PSNR reveals that the proposed algorithm performs better than the other existing methods in terms of noise removal and edge preservation.