Wavelet packet decompositions generalize the classical pyramidal wavelet structure. We use the vast amount of possible wavelet packet decomposition structures to create a secret wavelet domain and discuss how this idea can be used to improve the security of watermarking schemes. Two methods to create random wavelet packet trees are discussed and analyzed. The security against unauthorized detec...

posed both spatially (S) and spectrally (F). The spatial decomposition is carried out using a quad-tree split. Since the spatial partitions do not overlap, this segmentation allows the four children nodes to be further analyzed independently. The frequency decomposition is performed using a four channel quadrature mirror filter (QMF) bank. This produces a library of wavelet packet bases which c...

A non-uniform speech segmentation method based on wavelet packet transform is used for the localisation of phoneme boundaries. Eleven subbands are chosen by applying the mean best basis algorithm. Perceptual scale is used for decomposition of speech via Meyer wavelet in the wavelet packet structure. A real valued vector representing the digital speech signal is decomposed into phone-like units ...

Inspired by both the multilayer perceptron (MLP) and wavelet decomposition, Zhang and Benveniste proposed the wavelet MLP (W-MLP), which has been usedfor time series prediction. The wavelet packet MLP (WP-MLP) is an MLP with the wavelet packet as a feature extraction method to obtain time-frequency information. The WPMLP has been successfully applied to biomedical, image and speech classificati...

Image compression methods that use wavelet transforms have been successful in providing high rates of compression while maintaining good image quality. Even superior to these wavelet techniques are methods based on wavelet packet decompositions. When processing satellite data the amount of data suggests to use a parallel approach. Wavelet packet decomposition with best basis selection is implem...

In this paper, we introduce the notion of biorthogonal wavelet packets associated with nonuniform multiresoltion analysis and study their characteristics by means of Fourier transform. Three biorthogonal formulas regarding these wavelet packets are established. Moreover, it is shown how to obtain several new Riesz bases of the space (R) by constructing a series of subspaces of these nonuniform ...

The classification of transient timevarying electroencephalography (EEG) is quite important for further understanding the brain function. In order to classify different kinds of nonstationary EEG rhythms, wavelet packet analysis is used for designing sub-band filters with specified band-passed characteristics. Four kinds of wavelet packet decomposition using Daubechies wavelet are employed to i...