Abstract
The wavelet decomposing levels and the selection of the thresholding function affect the performance of image denoising using the wavelet thresholding method. In this paper, a new method to identify the wavelet decomposing levels using the 2D Haar wavelet thresholding method is presented to denoise an image. It uses the standard deviation values of the sub-bands to find out if the signal energy is strong or weak in the high frequency sub-bands after the 2D Haar wavelet transform. In addition, a new thresholding function is proposed which achieves better denoising performance in terms of peak signal-to-noise ratio (PSNR) and mean squared error (MSE) than the soft thresholding method. Especially, at high noise levels, the proposed new thresholding method outperforms hard thresholding, soft thresholding and semi-soft thresholding methods.