Wavelet based nonlinear image enhancement for Gaussian and uniform noise

In this paper we consider image enhancement by using a wavelet based nonlinear filtering scheme. It is well-known that the wavelet transform decomposes an image into a finite number of resolution scales that is very suitable for image analysis and image compression. Such a resolution decomposition is also useful for noisy image enhancement, in view of that the visible noise can be suitably separated in the low-frequency (LF) component and the high-frequency (HF) components of a wavelet transform. While the wavelet transform is used for the decomposition and reconstruction of images, we apply nonlinear piecewise-quadratic (PWQ) filters for the processing of the decomposed progressive wavelet HF components before reconstruction. We show by simulations that such a filtering scheme can achieve a considerable improvement in noise smoothing, details-preserving and the visual quality of images.