Wavelet packet decompositions based on tree structured 2-channel filter banks with conjugate quadrature filters (CQF) have recently found many applications in the area of audio coding. Their time-frequency tiling is dual to that of timevarying modulated lapped transforms (MLT). In this paper we present a new orthonormal wavelet packet basis, which is constructed by frequency-varying MLT. These ...

In this paper, a transform based methodology is presented for compression of electrocardiogram (ECG) signal. The methodology employs different transforms such as Discrete Wavelet Transform (DWT), Fast Fourier Transform (FFT) and Discrete Cosine Transform (DCT). A comparative study of performance of different transforms for ECG signal is made in terms of Compression ratio (CR), Percent root mean...

We present new multiwavelet transforms of multiplicity 2 for manipulation of discrete-time signals. The transforms are implemented in two phases: 1) Pre (post)-processing, which transforms the scalar signal into a vector signal (and back) and 2) wavelet transforms of the vector signal. Both phases are performed in a lifting manner. We use the cubic interpolatory Hermite splines as a predicting ...

this article introduces a systematic study for computational aspects of classical wavelet transforms over finite fields using tools from computational harmonic analysis and also theoretical linear algebra. we present a concrete formulation for the frobenius norm of the classical wavelet transforms over finite fields. it is shown that each vector defined over a finite field can be represented as...

Contents Preface ix 1. Wavelet and frame transforms originated from continuous and discrete splines, Amir Z. Averbuch and Valery A. Zheludev 1 1.1. Introduction 1 1.2. Preliminaries 4 1.3. Prediction filters originated from splines 9 1.4. Biorthogonal wavelet transforms generated by filter banks with downsampling factor N = 2 (diadic transforms) 17 1.5. Application of spline-based wavelet trans...

Recovering a signal (function) from finitely many binary or Fourier samples is one of the core problems in modern medical imaging, and by now there exist plethora methods for recovering such samples. Examples methods, which can utilise wavelet reconstruction, include generalised sampling, infinite-dimensional compressive sensing, parameterised-background data-weak (PBDW) method etc. However, an...

This paper describes an approach for texture characterization based on various wavelet decomposition transforms and its application for the discrimination of visually similar renal stone images. The proposed feature extraction algorithm applies Daubechies, Symlet, Coieflet, orthogonal and reverse biorthogonal wavelet transforms and uses approximation and detail coefficients to characterize rena...

Wavelet transforms and other multi-scale analysis functions have been used for compact signal and image representations in de-noising, compression and feature detection processing problems for about twenty years. Numerous research works have proven that space-frequency and spacescale expansions with this family of analysis functions provided a very efficient framework for signal or image data. ...

Wavelet transforms for discrete-time periodic signals are developed. In this nite-dimensional context, key ideas from the continuous-time papers of Daubechies and of Cohen, Daubechies, and Feauveau are isolated to give a concise, rigorous derivation of the discrete-time periodic analogs of orthonormal and symmetric biorthogonal bases of compactly supported wavelets. These discrete-time periodic...