Time scale dependence on the working nature of wavelet analysis makes it a valuable tool for Hurst parameter estimation. Similar to other wavelet-based signal processing applications, the selection of a particular wavelet type and vanishing moment in wavelet based Hurst estimation is a challenging problem. In this paper, we investigate the best Daubechies wavelet in wavelet based Hurst estimati...

The objective of this study is to propose multiresolution data fusion scheme using multiresolution analysis (MRA). Three techniques compared, respectively based on Haar wavelet basis (HWB), Daubechies wavelet basis (DWB), and IHS transform. Daubechies Wavelet Basis (DWB) is far more efficient than the HWB and IHS transform, thus establishing the advantages for data fusion of formally multiresol...

Compression is an important part in image processing in order to save memory space and reduce the bandwidth while transmitting. The main purpose of this paper is to analyse the performance of 3-D wavelet encoders using 3-D medical images. Four wavelet transforms, namely, Daubechies 4,Daubechies 6,Cohen-Daubechies-Feauveau 9/7 and Cohen Daubechies-Feauveau5/3 are used in the first stage with enc...

ÐThis paper studies the effects of image translation on wavelet-based image registration. The main result is that the normalized correlation coefficients of low-pass Haar and Daubechies wavelet subbands are essentially insensitive to translations for features larger than twice the wavelet blocksize. The third-level low-pass subbands produce a correlation peak that varies with translation from 0...

Wave Cluster is a grid based clustering approach. Many researchers have applied wave cluster technique for segmenting images. Wave cluster uses wave transformation for clustering the data item. Normally it uses Haar, Daubechies and Cohen Daubechies Feauveau or Reverse Bi-orthogonal wavelets. Symlet, Biorthogonal and Meyer wavelet families have been used in this paper to compare its clustering c...

In this article, we discuss wavelet versions of nonparametric curve estimators and weighted least squares wavelet regression. We introduce a modi ̄ed wavelet version of the Gasser-MÄ uller estimator that is unbiased whenever a wavelet representation of the nonparametric response curve correctly speci ̄es the response. In some cases, involving the Daubechies wavelet system, we ̄nd that the modi ̄ed ...

A wavelet Galerkin finite-element method is proposed by combining the wavelet analysis with traditional finite-element method to analyze wave propagation phenomena in fluid-saturated porous medium. The scaling functions of Daubechies wavelets are considered as the interpolation basis functions to replace the polynomial functions, and then the wavelet element is constructed. In order to overcome...

This paper presents a study in an efficient methodology for analysis and characterization of digital images psoriasis lesions using Daubechies D8 wavelet technique. The methodology is based on the transformation of 2D Discrete Wavelet Transform (DWT) algorithm for Daubechies D8 at first level to obtain the coefficients of the approximations and details sub-images. For classification method, sta...