Wavelet Transform for Image Noise Reduction

The search for efficient image denoising methods still is a valid challenge, at the crossing of functional analysis and statistics. In spite of the sophistication of the recently proposed methods, most algorithms have not yet attained a desirable level of applicability. All show an outstanding performance when the image models corresponds to the algorithm assumptions, but fails in general and creates artifacts or remove image fine structures. The primary goal of noise reduction is to remove the noise without losing much detail contained in an image. To achieve this goal, we make use of a mathematical function known as the wavelet transform to localize an image into different frequency components or useful subbands and effectively reduce the noise in the subbands according to the local statistics within the bands.