This technical paper deals with the application of the Wavelet Transform to the study of evoked potentials. In particular, Wavelet Transform gives an optimal time-dependent frequency decomposition of the evoked responses, something difficult to be achieved with previous methods such as the Fourier Transform. We describe in detail the protocol for implementing the decomposition based on the Wave...

This paper presents Mean Best Basis algorithm, an extension of the well known Best Basis Wickerhouser’s method, for an adaptive wavelet decomposition of variable-length signals. A novel approach is used to obtain a decomposition tree of the wavelet-packet cosine hybrid transform for speech signal feature extraction. Obtained features are tested using the Polish language hidden Markov model phon...

A simple construction of an orthonormal basis starting with a so called mother wavelet, together with an efficient implementation gained the wavelet decomposition easy acceptance and generated a great research interest in its applications. An orthonormal basis may not, however, always be a suitable representation of a signal, particularly when time (or space) invariance is a required property. ...

Recently, we have been developing general multireso-lution signal decomposition schemes that unify traditional (linear) approaches and allow use of nonlinear ltering techniques in the decomposition. This paper summarizes our approach and provides several simple examples. Some of these examples are known in the literature (e.g., Haar pyramid and wavelet) and some of them are new (e.g., morpholog...

Abstract— This paper proposes an image compression scheme using a personalized storage Discrete Wavelet Transform (DWT). In image compression schemes based on DWT, the module that generates these wavelet coefficients is sequentially attached to some encoding bitplanes. As the level of DWT decomposition increases the quantity of bits required to represent the wavelet coefficients is increased. A...

In this article a texture feature extrac tion 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 underly ing principle is based on the fact that di erent im age regions exhibit di erent textures Since most signi cant information of a texture often lies in t...

The precision agriculture decision-making needs of geographic information visualization analysis for farmland. In order to get 3D visualization of farmland, the Matlab software and wavelet transform were used for 3Dterrain survey data processing. Haar, DB6, Sym8, coif3 wavelet were used on the 3 layer decomposition of elevation data de-noising test, DB6 wavelet was used on the two to seven laye...

Introduction: Brain visual evoked potential (VEP) signals are commonly known to be accompanied by high levels of background noise typically from the spontaneous background brain activity of electroencephalography (EEG) signals. Material and Methods: A model based on dyadic filter bank, discrete wavelet transform (DWT), and singular value decomposition (SVD) was developed to analyze the raw data...

A good watermarking scheme should be able to perform equally well on all types of images irrespective of image contents because practically watermarking has to be applied to images of all types. In this paper, it is shown that in wavelet based spread spectrum technique, watermarking at level 1 decomposition is better for textured images while watermarking at level 2 decomposition is better for ...

De-noising and extraction of the weak signature are crucial to fault prognostics in which case features are often very weak and masked by noise. The wavelet transform has been widely used in signal de-noising due to its extraordinary time-frequency representation capability. In this paper, the performance of wavelet decomposition-based de-noising and wavelet filter-based de-noising methods are ...