This thesis studies the application of signal-adaptive lter banks in perceptual coding of audio with an emphasis on Wavelet Filter Banks (WFB). It provides an overview of perceptual coding of audio, the motivating psychoacoustic principles, transforms and wavelet theory. Additionally, di erent existing wavelets-based audio coding schemes are presented. The aim of most of the schemes is to overc...

A dynamic adaptive numerical method for solving partial differential equations on the sphere is developed. The method is based on second generation spherical wavelets on almost uniform nested spherical triangular grids, and is an extension of the adaptive wavelet collocation method to curved manifolds. Wavelet decomposition is used for grid adaption and interpolation. An OðN Þ hierarchical fini...

Measurement of the oil-water flow is of great importance in the industrial process. In the paper, a soft-measurement method for oil-water mass flow-rate was brought forward, in which the V-cone differential pressure meter was used and the adaptive wavelet network was developed to achieve the soft-measurement of the mass flow-rate. The multi-input single output model of adaptive wavelet network ...

In this paper, we propose image restoration algorithms based on adaptive wavelet–domain statistical models. We present a method to estimate the model parameters from the observations, and solve the restoration problem in orthonormal and translation-invariant wavelet domains. Substantial improvements over previous wavelet–based restoration methods are obtained. The use of a translation-invariant...

wavelet shrinkage denoising approach is able to maintain local regularity of a signal while suppressing noise. However, the conventional wavelet shrinkage based methods are not timescale adaptive to track the local timescale variation. In this paper, a new type of Neural Shrinkage (NS) is presented with a new class of shrinkage architecture for speckle reduction in Synthetic Aperture Radar (SAR...

This papers gives an overview of wavelet transforms application to signal denoising problem. Wavelets perform well for this application and have been used before with great success. To further improve the transform efficiency adaptivity is introduced to traditional wavelet transforms. The lifting framework as a method to construct wavelets facilitates the effort to develop efficient adaptation ...

Deblurring in the presence of noise is a hard problem, especially in ultrasonic and CT images. In this paper, we propose a new method of image deblurring in presence of noise, using symmetric Daubechies complex wavelet transform. The proposed method is based on shrinkage of multilevel Daubechies complex wavelet coefficients, and is adaptive as it uses shrinkage function based on the variance of...

Reconstruction of the refractive index fluctuations in the atmosphere, or atmospheric tomography, is an underlying problem of many next generation adaptive optics (AO) systems, such as the multiconjugate adaptive optics or multiobject adaptive optics (MOAO). The dimension of the problem for the extremely large telescopes, such as the European Extremely Large Telescope (E-ELT), suggests the use ...

A simultaneous space-time variational formulation of a parabolic evolution problem is solved with an adaptive wavelet method. This method is shown to converge with the best possible rate in linear complexity. Thanks to the use of tensor product bases, there is no penalty in complexity due to the additional time dimension. Special wavelets are designed such that the bi-infinite system matrix is ...

This paper describes a new multilevel decomposition method for the separation of convolutive image mixtures. The proposed method uses an Adaptive Quincunx Lifting Scheme (AQLS) based on wavelet decomposition to preprocess the input data, followed by a Non-Negative Matrix Factorization whose role is to unmix the decomposed images. The unmixed images are, thereafter, reconstructed using the inver...