De-Noising of Image Using Adaptive Thresholding Technique

This paper describes a computationally m o r e efficient and adaptive threshold e s t i m a t i o n method for image de-noising in the wavelet domain based on Generalized Gaussian Distribution (GGD) modelling of sub band coefficients. In this 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. The noisy image is first decomposed into many levels to obtain different frequency bands. Then soft thresholding method is used to remove the noisy coefficients, by fixing the optimum thresholding value 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). Here, in this paper, the role of wavelet based image de-noising by adaptive thresholding technique is discussed.