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...

ORTHOGONAL AND SYMMETRIC HAAR WAVELETS ON THE THREE-DIMENSIONAL BALL Andy Chow Master of Science Graduate Department of Computer Science University of Toronto 2010 Spherical signals can be found in a wide range of fields, including astronomy, computer graphics, medical imaging and geoscience. An efficient and accurate representation of spherical signals is therefore essential for many applicati...

Wavelet-based algorithm for image compression with multilevel unequal error protection (UEP) codes in wide-band code division multiple access (W-CDMA) system over additive white Gaussian noise (AWGN) and Rayleigh fading channels are analysed. The utilization of Wavelets has come out to be a robust method for compress image/video sequence. The wavelet transform compression technique has shown to...

Shannon’s rate distortion theory demonstrates that the optimal distortion rate can be achieved by quantizing blocks of arbitrary large dimensions. In practice, however, most image compression coders rely on the principle of transform coding combined with scalar quantization and lossless coding. Transform coding consists in applying a linear transformation to an N-dimensional block of data. The ...

The WSO M (Wavelet SelfOrganizing 1\Jap) model, a rwural network for the erea.tion of wavelet bases adapted to the distribution of input data, is introduced. The model provides an efficient on-lim) way to construct high-dimensional wavelet bases. Simulations of a lD function approximation problem illustrate how WSOM adapts to non-uniformly distributed input data, outperforming the discrete wa.v...

Extended Abstract. Forecasting is one of the most important purposes of time series analysis. For many years, classical methods were used for this aim. But these methods do not give good performance results for real time series due to non-linearity and non-stationarity of these data sets. On one hand, most of real world time series data display a time-varying second order structure. On th...

The computation of sparse representations of data on the sphere (as e.g. topographical data) is a crucial step for further processing such as multiple separation, migration, imaging and sparsity promoting data-recovery. The Easy Path Wavelet Transform (EPWT) is a new tool for sparse data representation that has recently been introduced for image compression. In this paper we consider the EPWT o...

In this work, a novel ECG data compression method is presented which employs set partitioning in hierarchical trees algorithm(SPIHT) on two dimensional electrocardiogram(2D-ECG).The 2D ECG is a two dimensioned array, in which each row of this array indicates one or more period and amplitude[7] normalized ECG beats. When SPIHT algorithm is used to compress one or two-dimensional signals separate...