Overcomplete discrete wavelet transforms (ODWT) are used in a number of applications because they provide shift invariance, a property extremely useful in wavelet-based image processing and video coding. In this paper, we propose a new construction of the ODWT starting from the subbands of the critically-sampled (complete) DWT. The most straightforward application of our theory is scalable vide...

This paper presents time-frequency multiresolution wavelet analysis on power system transients. Since it is difficult to analyze transients on-site due to a vast amount of data recorded from a digital transient recorder, it is imperative to develop an intelligent recorder which has the ability to detect and classify different types of power system transients. In order to develop a good approach...

In the paper, the possibility of detection the hidden defects or damage applying the models of dynamic (active) infrared thermography and the 2D discrete wavelet transform of data measured in thermal processes has been described. The possibility to examine the defects of the material structure with the discrete wavelet transform (DWT) of the spatial function registering the disturbance underwen...

The ARSIS concept is meant to increase the spatial resolution of an image without modification of its spectral contents by merging structures extracted from a higher resolution image of the same scene but in a different spectral band. It makes use of wavelet transforms and multiresolution analysis. It is currently applied in an operational way with dyadic wavelet transforms that limit the mergi...

Noise reduction in speech signals is a growing area that encountered several applications like communication channel transmission, automatic speech recognition, telephony and hearing aids, among others. This paper introduces a technique for noise reduction in speech signals that combines both Discrete-time Kalman filtering and Wavelet transforms. While filtering provides noise reduction, Wavele...

: Image compression may be lossy or lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics. Lossy compression methods, especially when used at low bit rates, introduce compression artifacts. Lossy methods are especially suitable for natural images such as photographs in applications where minor (sometimes impercep...

Wavelet transforms have started to receive increasing attention due to their wide applications in image and signal processing, and due to the recent discovery of a fast sequential algorithm for discrete wavelet transforms by Mallat[Mal89]. In this paper we present a mapping of the wavelet operations onto the MasPar massively parallel single instruction multiple data (SIMD) computer [Bla90], [Ma...

In this paper we present orthogonal overlapped block transforms as a frame synchronized signal analysis tool with the capability of arbitrary multiresolution time-spectral decomposition of speech signals. Our prime interest is in the representation of nonstationary discrete-time signals in terms of wavelet packets, and we concentrate on their fast transform algorithms. Wavelet packet representa...

Spatial and/or temporal variabilities of clouds is of paramount importance for at least two intensely researched sub-problems in global and regional climate modeling: • cloud-radiation interaction where correlations can trigger three-dimensional (3D) radiative transfer effects; and • dynamical cloud modeling where the goal is to realistically reproduce the said correlations. We propose wavelets...

In this paper, we present a new approach to deal with the noise inherent in the microarray image processing procedure. We use the denoising capabilities of decimated and undecimated multiwavelet transforms, DMWT and UMWT respectively, for the removal of noise from microarray data. Multiwavelet transforms, with appropriate initialization, provide sparser representation of signals than wavelet tr...