Discrete Wavelet Domain Research Articles

A Semi-Fragile Watermarking Scheme Using Weighted Vote with Sieve and Emphasis for Image Authentication

This paper describes a semi-fragile watermarking scheme for image authentication and tamper-proofing. Each watermark bit is duplicated and randomly embedded in the original image in the discrete wavelet domain by modifying the corresponding image coefficients through quantization. The modifications are made so that they have little effect on the image and that the watermarking is robust against tampering. The watermark image for authentication is reconstructed by taking a weighted vote on the extracted bits. The bits that lose the vote are treated as having been tampered with, and the locations of the lost bits as indicating tampered positions. Thus, authentication and tamper-proofing can be done by observing the images of watermarks that win and lose votes. Sieving, emphasis, and weighted vote were found to be effectively make the authentication and tamper detection more accurate. The proposed scheme is robust against JPEG compression or acceptable modifications, but sensitive to malicious attacks such as cutting and pasting.

Speech Quality Evaluation: A New Application of Digital Watermarking

Speech quality evaluation is an important research topic. The traditional way for speech quality evaluation is using subjective tests. They are reliable, but very expensive, time consuming, and cannot be used in certain applications such as online monitoring. Objective models, based on human perception, were developed to predict the results of subjective tests. The existing objective methods require either the original speech or complicated computation model, which makes some applications of quality evaluation impossible. In this paper, we propose a novel speech quality evaluation method using digital watermarking. Our algorithm evaluates the speech quality without the need of reference speech or any computational model. The watermark is embedded in the discrete wavelet domain or temporal domain of a speech signal by using quantization technique. This algorithm can evaluate perceptual quality of speech that is distorted by Gaussian noise, MP3 compression, low-pass filtering, and packet loss. The experimental results show that the method yields accurate quality scores which are very close to the results of the perceptual evaluation of speech quality

Adaptive Hurst Index Estimator Based on Wavelet

The measurement studies show that the burstiness of packet traffic in LAN as well as WAN is associated with self-similar and long-range dependency, and Hurst index is the key value of this model representing the burstiness of traffic. With the analysis in discrete wavelet domain, the nature of the wavelet coefficients and their statistical properties are proposed. Then an adaptive, efficient unbiased estimator of Hurst index based on multiresolution wavelet analysis and weighted regression is presented. Simulation results based on fractal Gaussian noise and real traffic data reveal the proposed approach shows more adaptiveness, accuracy and robustness than traditional estimators which has only O(N) computation. Thus this estimator can be applied to the application of traffic management and real-time control in high-speed networks.

Models for correlated multifractal hypersurfaces.

We discuss and implement computer approximations of fractal and multifractal hypersurfaces. These hypersurfaces consist of reconstructions of a stochastic process in the real space from randomly distributed variables in the discrete wavelet domain. The synthetic surfaces have the usual fractional Brownian motion as a particular case, and inherit the correlation structure of these fractals. We first introduce the one-dimensional version of these surfaces that obey a weak self-affine symmetry. This symmetry appears in the wavelet domain as a condition on the second moments of the probability distributions of the wavelet coefficients. Then we use these relations to define the fractals and multifractals in d dimensions. Finally, we concentrate on the generation of samples of these hypersurfaces.

Digital watermarking for telltale tamper proofing and authentication

In this paper, we consider the problem of digital watermarking to ensure the credibility of multimedia. We specifically address the problem of fragile digital watermarking for the tamper proofing of still images. Applications of our problem include authentication for courtroom evidence, insurance claims, and journalistic photography. We present a novel fragile watermarking approach which embeds a watermark in the discrete wavelet domain of the image by quantizing the corresponding coefficients. Tamper detection is possible in localized spatial and frequency regions. Unlike previously proposed techniques, this novel approach provides information on specific frequencies of the image that have been modified. This allows the user to make application-dependent decisions concerning whether an image, which is JPEG compressed for instance, still has credibility. Analysis is provided to evaluate the performance of the technique to varying system parameters. In addition, we compare the performance of the proposed method to existing fragile watermarking techniques to demonstrate the success and potential of the method for practical multimedia tamper proofing and authentication.

Optimization of signal denoising in discrete wavelet transform

A method to optimize the parameters used in signal denoising in the wavelet domain is presented. The method, which is based on cross-validation (CV) procedure, permits to select the best decomposition level and the best wavelet filter function to denoise a signal in the discrete wavelet domain. The procedure was validated by using computer generated signals to which white noise was added. Signals having different features and a range of signal to noise ratios were explored. The method was shown to give reliable results for all cases studied. The proposed method was applied to experimental gravitation field flow fractionation records, and the results were compared with classical low pass filtering in the Fourier domain.

Power system transient and harmonic studies using wavelet transform

This paper presents the application of wavelet transforms in power system transient and harmonic analyses. Based on the discrete time domain approximation, the system components such as resistors, inductors and capacitor are modeled respectively in the discrete wavelet domain for the purpose of transient and steady state analyses. Since the power system is described by a set of ordinary differential equations, an initial value of the state variable is considered for the transient analysis, while a periodic condition is applied to the state variable for the steady state analysis. The wavelet domain impedance is set up, and the equivalent circuit is thus built for system simulation. This method can be implemented by any kind of orthogonal wavelet transform. Numerical results from an arc furnace system are also presented for the transient, harmonic and time-frequency analyses.