In this paper, we discuss the B-spline wavelets introduced by Chui and Wang in [1]. The definition for B-spline wavelet packets is proposed along with the corresponding dual wavelet packets. The properties of B-spline wavelet packets are also investigated.

The Paper Adaptive Nonseparable Wavelet Transform via Lifting and its Application to Content-Based Image Retrieval. Adapt a multidimensional wavelet filter bank, based on the nonseparable lifting scheme framework. The lifting scheme there are two linear filter denoted P (prediction) and U ( update) are defined as Neville filters of order N and N ~ , respectively. We are applying the Haar wavele...

It is known that signals obtained from the real world environment are corrupted by the noise. This noise causes poor performance of the relevant system and therefore must be removed effectively before further processing of signal. Research in the area of wavelets showed that wavelet shrinkage method performs well and efficiently as compared to other methods of denoising. In this paper, a compar...

In this article we study function estimation via wavelet shrinkage for data with long-range dependence. We propose a fractional Gaussian noise model to approximate nonparametric regression with long-range dependence and establish asymp-totics for minimax risks. Because of long-range dependence, the minimax risk and the minimax linear risk converge to zero at rates that diier from those for data...

In this article we study function estimation via wavelet shrinkage for data with long-range dependence. We propose a fractional Gaussian noise model to approximate nonparametric regression with long-range dependence and establish asymp-totics for minimax risks. Because of long-range dependence, the minimax risk and the minimax linear risk converge to zero at rates that diier from those for data...

Recently, several wavelet transform based image coding techniques are reported in literature. Though these schemes yield very low bit rates, they suffer from the drawback of computational complexity. There is always a need for simple, fast and easy to implement image coding techniques that yield good subjective quality at low bitrates. To obtain good data compression, the wavelet transform coef...

In this paper, we present a direct solution method based on wavelet networks for image compression. Wavelet networks are a combination of radial basis function (RBF) networks and wavelet decomposition, where radial basis functions were replaced by wavelets. The results show that the wavelet networks approach succeeded to improve high performances in terms of compression ratio and reconstruction...

This paper presents a non-linear filtering method based on the multiresolution analysis of the Discrete Wavelet Transform (DWT). The main idea is to use the time-frequency localization properties of the wavelet decomposition. The proposed algorithm is using an extra decomposition of the identified noise in order to reduce the correlation between the electrocardiogram (ECG) signal and noise. The...

The aim of this study is to compare the Discrete wavelet decomposition and the modified Principal Analysis Component (PCA) decomposition to analyze the stabilogram for the purpose to provide a new insight about human postural stability. Discrete wavelet analysis is used to decompose the stabilogram into several timescale components (i.e. detail wavelet coefficients and approximation wavelet coe...