Applications of Multiscale Transforms to Image Denoising: Survey

Abstract

Image denoising is one of the classical problems in digital image processing and has been studied for nearly half a century due to its important role as a pre-processing step in various electronic imaging applications. The search for efficient image denoising methods is still a valid challenge. 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 model corresponds to the algorithm assumptions but fail in general and create artifacts or remove image fine structures. This paper surveys a comparison of the discriminating power of the various multiresolution based thresholding techniques mainly wavelet and curvelet transform for image denoising.