An Improved Method of Image Denoising Base on Stationary Wavelet

This work describes a computationally more efficient and adaptive threshold estimation method for image denoising in the stationary wavelet domain. In this proposed method, the choice of the threshold estimation is carried out by analyzing the statistical parameters of the wavelet sub band coefficients like standard deviation, arithmetic mean and geometrical mean. Then novel threshold method is used to remove the noisy coefficients, by combing the soft-thresholding and hard-thresholding by the proposed method. Experimental results on several test images by using this method show that this method yields significantly superior image quality and better Peak Signal to Noise Ratio (PSNR).