This review article provides a comprehensive survey on state-of-the-art impulse and
Gaussian denoising filters applied to images and summarizes the progress that has been …

Ultrasonography is non-invasive and painless. In Ultrasonography the images are often
affected with Speckle noise. It is a multiplicative noise. To help the doctors to identify the …

The method of wavelet thresholding for removing noise, or denoising, has been researched
extensively due to its effectiveness and simplicity. Much of the literature has focused on …

The granular appearance of speckle noise in synthetic aperture radar (SAR) imagery makes
it very difficult to visually and automatically interpret SAR data. Therefore, speckle reduction …

In this paper, we present a wavelet-based despeckling method for synthetic aperture radar
images and derive a Bayesian wavelet shrinkage factor to estimate noise-free wavelet …

A generalized multidimensional Wiener filter for denoising is adapted to hyperspectral
images (HSIs). Commonly, multidimensional data filtering is based on data vectorization or …

In breast cancer diagnosis, the radiologists mainly use their eyes to discern cancer when
they screen the mammograms. However, in many cases, cancer is not easily detected by the …

The paper presents a novel despeckling method, based on Daubechies complex wavelet
transform, for medical ultrasound images. Daubechies complex wavelet transform is used …

Wavelet domain denoising has recently attracted much attention, mostly in conjunction with
the coefficient-wise wavelet shrinkage proposed by Donoho (see IEEE Trans. Inform …

This paper describes wavelet thresholding for image denoising under the framework
provided by statistical learning theory aka Vapnik-Chervonenkis (VC) theory. Under the …