in this paper we present a method to perform flood frequency analysis (ffa) when the assumption of stationary is not important (or not valid). a wavelet transform model is developed to ffa. a full series is applied to ffa using two different wavelet functions, and then a combined method is investigated. in the combined method, all discharge data which were less than the lowest value of annual m...

In this article a texture feature extraction scheme based on M-band wavelet packet frames is investigated. The features so extracted are used for segmentation of satellite images which usually have complex and overlapping boundaries. The underlying principle is based on the fact that different image regions exhibit different textures. Since most signifcant information of a texture often lies in...

To optimize the number of decomposition layers in wavelet threshold denoising for ultrasonic signals, we propose a self-adaptive algorithm of determining the number of decomposition layers based on singular spectrum analysis and wavelet entropy. First the noise-containing signals are decomposed by discrete wavelet transform. The slope of the singular value spectrum for each layer is estimated. ...

This work is based on the comparative study of different decomposition methods used to de-noise an ECG signal. There are several signal processing techniques available like Fourier Transform method, Short Term Fourier Transform method, Wavelet analysis, Empirical Mode of Decomposition method etc. Though Fourier Transform method is predominantly used for decomposition purpose but it is not suita...

Classical discrete wavelet packet transforms are sensitive to changes in image orientation and translation. Therefore, it is hardly possible to extract rotation invariant features from images in the transform domain. This paper proposes several algorithms for invariant discrete wavelet decomposition to produce an invariant representation for an image. The procedure can be divided into several s...

Results of lossy image compression using wavelet transforms and several thresholding techniques are presented here. The analyzed image was divided into little sub-images and each one was decomposed in a vector following a Hilbert fractal curve. The wavelet transform was applied to each vector and some of the high frequency components were suppressed based on some threshold criteria. Different l...

In this paper the faults diagnosis of induction machines based on the discrete wavelet transform (DWT) is detailed. The wavelet decomposition is used to extract the information from a signal over a wide range of frequencies. This analysis is performed in both time and frequency domains. The Daubechies wavelet is selected for the analysis of the stator current. Wavelet components appear to be us...

In this paper, a new satellite image contrast enhancement technique based on s Atrous wavelet transform and singular value decomposition (SVD) has been proposed. To obtain shift invariant discrete wavelet transform decomposition for images, we introduced the discrete wavelet transform known a “A trous” algorithm to decompose the image into wavelet planes which is computed as the difference betw...

The efficiency of all Zerotree coding algorithms relay on the "decaying spectrum" hypothesis: a wavelet coefficient within a certain frequency scale of a wavelet subband decomposition has a larger magnitude than all his descendants (coefficients situated in higher frequency scales having the same spatial orientation). The higher the percentage this hypothesis is satisfied, the better are the re...

The research aimed to introduce newly designed features for speech signal. The newly developed features are designed to normalize the dynamic structure of best tree decomposition of wavelet packets. The 4 points encoded vector is a full of information just like the original best tree’s structure. It is a loss less encoding system that grantees 100% reconstruction of the original best tree. The ...