The dual-tree complex wavelet transform (CWT) is a relatively recent enhancement of the discrete wavelet transform (DWT) with important additional properties: It is nearly shift-invariant and directionally selective in two and higher dimensions. It achieves this with a redundancy factor of only 2 for d-dimensional signals, which is substantially lower than the undecimated DWT. The multidimensio...

This paper develops two new adaptive wavelet transforms based on the lifting scheme. The lifting construction exploits a spatialdomain, prediction-error interpretation of the wavelet transform and provides a powerful framework for designing customized transforms. We use the lifting construction to adaptively tune a wavelet transform to a desired signal by optimizing data-based prediction error ...

Let  $varpi$ be a representation of the homogeneous space $G/H$, where $G$ be a locally compact group and  $H$ be a compact subgroup of $G$. For  an admissible wavelet $zeta$ for $varpi$  and $psi in L^p(G/H), 1leq p <infty$, we determine a class of bounded  compact operators  which are related to continuous wavelet transforms on homogeneous spaces and they are called localization operators.

electrocardiogram (ecg) is one of the most common biological signals which plays a significant role in diagnosis of heart diseases. one of the most important parts of ecg signal processing is interpretation of qrs complex and obtaining its characteristics. r wave is one of the most important sections of this complex which has an essential role in diagnosis of heart rhythm irregularities and als...

The main aim of this paper is to propose a technique for enhancing contrast of the dark images using Undecimated Balanced GHM multi wavelet transform (UMWT) and Dynamic Stochastic Resonance (DSR). The DSR based approach utilizes the inherent noise of an image for enhancement. Darkness due to inadequate illumination is treated as noise, and is used to yield a noise induced adjustment of the imag...

The main aim of this paper is to propose a technique for enhancing contrast of the dark images using Undecimated Balanced GHM multi wavelet transform (UMWT) and Dynamic Stochastic Resonance (DSR). The DSR based approach utilizes the inherent noise of an image for enhancement. Darkness due to inadequate illumination is treated as noise, and is used to yield a noise induced adjustment of the imag...

A novel undecimated wavelet transform based contrast enhancement algorithmisproposed to for both gray scale andcolor images. Contrast enhancement is realized by tuning the magnitude of approximation coefficients at each level with respect to the approximation coefficients of one higher level during the inverse transform phase in a center/surround enhancement sense.The performance of the propose...

The main aim of this paper is to propose a technique for enhancing contrast of the dark images using Undecimated Balanced GHM multi wavelet transform (UMWT) and Dynamic Stochastic Resonance (DSR). The DSR based approach utilizes the inherent noise of an image for enhancement. Darkness due to inadequate illumination is treated as noise, and is used to yield a noise induced adjustment of the imag...

The aim of this paper is to construct a model which decomposes a 3D image into two components: the first one containing the geometrical structure of the image, the second one containing the noise. The proposed method is based on a second order variational model and an undecimated wavelet thresholding operator. The numerical implementation is described, and some experiments for denoising a 3D MR...

Convolution is one of the most widely used digital signal processing operations. It can be implemented using the fast Fourier transform (FFT), with a computational complexity ofO(N logN). The undecimated discrete wavelet transform (UDWT) is linear and shift invariant, so it can also be used to implement convolution. In this paper, we propose a scheme to implement the convolution using the UDWT,...