This paper presents a memory efficient, high throughput parallel lifting based running three dimensional discrete wavelet transform (3-D DWT) architecture. 3-D DWT is constructed by combining the two spatial and four temporal processors. Spatial processor (SP) apply the two dimensional DWT on a frame, using lifting based 9/7 filter bank through the row rocessor (RP) in row direction and then ap...

In this paper, contrast enhancement of dark image using Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) coefficients is proposed. Then the contrast enhancement is obtained by applying Dynamic Stochastic Resonance (DSR).The goal of dark image enhancement is to clearly visualize the features of the image. Two different coefficients DCTand DWT are used for implementing contras...

In this paper, we develop a method of performing the one-point statistics of a perturbed density field with a multiresolutional decomposition based on the discrete wavelet transform (DWT). We establish the algorithm of the one-point variable and its moments in considering the effects of Poisson sampling and selection function. We also establish the mapping between the DWT one-point statistics i...

Discrete wavelet transform (DWT) is known for its signal processing ability. In the recent researches, DWT is adopted for signal filtering before executing dynamic data reconciliation. While on-line dynamic data reconciliation is concerned, the computation is heavy duo to the filtering in every time instant. In this article, a shift property of the DWT is indicated and is applied to reduce the ...

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of hu...

Standard DWT (Discrete Wavelet Transform), being non-redundant, is a very powerful tool for many non-stationary Signal Processing applications, but it suffers from three major limitations; 1) shift sensitivity, 2) poor directionality, and 3) absence of phase information. To reduce these limitations, many researchers developed real-valued extensions to the standard DWT such as WP (Wavelet Packet...

In many applications, old data in time series become less important as time elapses, which is a big challenge to traditional techniques for dimension reduction. To improve Discrete Wavelet Transform (DWT) for effective dimension reduction in this kind of applications, a new method, largest-latest-DWT, is designed by keeping the largest k coefficients out of the latest w coefficients at each lev...

EEG signals play significant role in the study of mental disorders. Epilepsy is one major disorders and need technological support treatment. A method proposed here an endorsement technique for epileptic seizures using electroencephalogram (EEG) captured non-invasive method. The uses power spectrum density discrete wavelet transformation (DWT). impact spectral analysis along with usage characte...

this paper presents a new coding method for image compression based on jpeg2000 and contourlet transform. jpeg2000 standard is a common standard that uses discrete wavelet transform (dwt) in the compression process. the main problems of dwt are failure to detect curved edges in image and its shortage representation of the ridge and furrow patterns which cause deficiency and block artifacts rema...