Anisotropic Wavelet-Based Image Denoising Using Multiscale Products

Images are often corrupted by noise in the process of acquisition and transmission. Thus, image denoising is a key issue in all image processing researches. The great challenge of image denoising is how to preserve the details of an image when reduces the noise. In this paper, a new denoising algorithm based on anisotropic wavelet transform (AWT) using multiscale products is proposed. Before denoising, the noisy images are first decomposed by the anisotropic wavelet. The multiscale product threshold is then applied to the multiscale products of the AWT coefficients instead of directly to the AWT coefficients. Since the multiplicating operation amplifies the significant features and dilute noise, the method reduces speckle effectively while preserving edge structures. Experimental results show that the proposed scheme can outperform standard wavelet-based denoising with soft and hard threshold. (c) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]