Wavelet Shrinkage and Denoising

Introduction to Wavelet Shrinkage and Denoising Procedure for wavelet shrinkage Why Wavelet Shrinkage Works Two methods of Wavelet Shrinkage An image is often corrupted by noise in its acquisition and transmission stage. Noises are normally created when scanning images to produce digital images, recording a voice to an audio file, and even transmitting digital image often produce Noise. This noise can be random or white noise with no coherence or coherent noise introduced by device mechanism Wavelet shrinkage is a signal denoising technique based on the idea of thresholding the wavelet coefficients. Denoising is the process of removing noise from a signal. Wavelet coefficients having small absolute values are considered to encode very fine details of the signal. Wavelet shrinkage denoising should not be confused with smoothing, Whereas smoothing removes high frequencies and retains low ones, denoising attempts to remove whatever noise is present and retain whatever signal is present regardless of the signals frequency content.