Methods based on thresholding of wavelet coefficients have been found to be popular in the estimation of biological signals from noisy environment. Hard and soft filters are most commonly used in these methods. In this paper a novel thresholding filter for wavelet shrinkage estimation of biological signals is proposed. The proposed novel filter is applied using Visu Shrink rule and top rule to ...

An improved pixon-based method is proposed in this paper for image segmentation. In thisapproach, a wavelet thresholding technique is initially applied on the image to reduce noise and toslightly smooth the image. This technique causes an image not to be oversegmented when the pixonbasedmethod is used. Indeed, the wavelet thresholding, as a pre-processing step, eliminates theunnecessary details...

This paper presents a spatial-correlation thresholding scheme for noise reduction by wavelet transform. Observing that edge structures are of high magnitude across wavelet scales but noise decays rapidly, we multiply two adjacent wavelet scales to form a spatial-correlation function to enhance significant structures and dilute noise. Dissimilar to the traditional thresholding schemes that apply...

A wavelet transform algorithm combined with a conjugate gradient method is used for the inversion of Poisson’s integral (downward continuation), used in airborne gravimetry applications. The wavelet approximation is dependent on orthogonal wavelet base functions. The integrals are approximated in finite multiresolution analysis subspaces. Mallat’s algorithm is used in the multiresolution analys...

Wavelet transforms enable us to represent signals with a high degree of scarcity. Wavelet thresholding is a signal estimation technique that exploits the capabilities of wavelet transform for signal denoising. The aim of this project was to study various thresholding techniques such as SureShrink, VisuShrink and BayeShrink and determine the best one for image denoising.

The partitioning of turbulent perturbations into a ‘‘low-dimensional’’ active part responsible for much of the turbulent energy and fluxes and a ‘‘high-dimensional’’ passive part that contributes little to turbulent energy and transport dynamics is investigated using atmospheric surface-layer (ASL) measurements. It is shown that such a partitioning scheme can be achieved by transforming the ASL...

in this paper, an efficient algorithm is proposed for detection of vertical root fractures (vrfs) in periapical (pa), and cone-beam computed tomography (cbct) radiographs of nonendodontically treated premolar teeth. pa and cbct images are divided into some sub-categories based on the fracture space between the two fragments as small, medium, and large for pas and large for cbcts. these graphics...

It is known that signals obtained from the real world environment are corrupted by the noise. This noise causes poor performance of the relevant system and therefore must be removed effectively before further processing of signal. Research in the area of wavelets showed that wavelet shrinkage method performs well and efficiently as compared to other methods of denoising. In this paper, a compar...

Orthogonal wavelet bases have recently been developed using multiple mother wavelet functions. Applying the discrete multiple wavelet transform requires the input data to be preprocessed to obtain a more economical decomposition. We discuss the properties of several prepro-cessing methods and their eeect on the thresholding results. We propose a multivariate thresholding method for multiwavelet...

Wavelet thresholding generally assumes independent, identically distributed normal errors when estimating functions in a nonparametric regression setting. VisuShrink and SureShrink are just two of the many common thresholding methods based on this assumption. When the errors are not normally distributed, however, few methods have been proposed. In this paper, a distribution-free method for thre...