The Discrete Wavelet Transform is the most powerful and new signal compression technique which uses multiresolution analysis for analyzing speech signal. Here we are doing parallel speech compression using two different wavelet transforms like Haar wavelets and Bi-orthogonal wavelet transformation (Bior). The resultant of components which are in high frequency bands are fusioned together and di...

we present here the numerical solution of damped forced oscillator problem using haar wavelet and compare the numerical results obtained with some well-known numerical methods such as runge-kutta fourth order classical and taylor series methods. numerical results show that the present haar wavelet method gives more accurate approximations than above said numerical methods.

Nonlinear diffusion filtering and wavelet shrinkage are two methods that serve the same purpose, namely discontinuity-preserving denoising. In this chapter we give a survey on relations between both paradigms when space-discrete or fully discrete versions of nonlinear diffusion filters are considered. For the case of space-discrete diffusion, we show equivalence between soft Haar wavelet shrink...

We propose a level-crossing A/D (LCA/D) converter which can be modelled with an oversampling A/D followed by a low resolution quantizer. In this paper we will study the reconstruction of non-bandlimited inputs processed by such a system and compare its performance to uniform sampling. Index Termslevel-crossing sampling, MSE, Haar wavelets, bitrate.

Figure 1: Multiple registered image channels are computed using various transformations of the input image; next, features such as local sums, histograms, and Haar wavelets are computed efficiently using integral images. Such features, which we refer to as integral channel features, naturally integrate heterogeneous sources of information, have few parameters, and result in fast, accurate detec...

Due to the extensive use of digital media applications, multimedia security and copyright protection has gained tremendous importance. Digital Watermarking is a technology used for the copyright protection of digital applications. In this project, a comprehensive approach for watermarking digital image is introduced. We propose a hybrid digital watermarking scheme based on Discrete Wavelet Tran...

This article defines and studies a new class of non-stationary random processes constructed from discrete non-decimated wavelets which generalizes the Cramér (Fourier) representation of stationary time series. We define an evolutionary wavelet spectrum (EWS) which quantifies how process power varies locally over time and scale. We show how the EWS may be rigorously estimated by a smoothed wavel...

Images require substantial storage and transmission resources, thus image compression is advantageous to reduce these requirements. The objective of this paper is to evaluate a set of wavelets for image compression. Image compression using wavelet transforms results in an improved compression ratio. Wavelet transformation is the technique that provides both spatial and frequency domain informat...

Wavelet shrinkage (WaveShrink) is a relatively new technique for nonparametric function estimation that has been shown to have asymptotic near-optimality properties over a wide class of functions. As originally formulated by Donoho and Johnstone, WaveShrink assumes equally spaced data. Because so many statistical applications (e.g., scatterplot smoothing) naturally involve unequally spaced data...

Nowadays, each newly produced car must conform to the appropriate safety standards and norms. The most direct way to observe how a car behaves during a collision and to assess its crashworthiness is to perform a crash test. This paper deals with the wavelet-based performance analysis of the safety barrier for use in a full-scale test. The test involves a vehicle, a Ford Fiesta, which strikes th...