Biorthogonal wavelet-based full-approximation schemes are introduced in this paper for the numerical solution of elasto-hydrodynamic lubrication line and point contact problems. The proposed methods give higher accuracy in terms of better convergence with low computational time, which have been demonstrated through the illustrative problems.

The field of image processing deals with a major issue, i.e., the suppression of noise from the wanted images. The intention of this message is to highlight some of the unique properties of spline wavelets. In this paper image denoising is performed using simulated noise images with various characteristics with the help of semi-orthogonal spline wavelets in comparison with CDF 9/7 wavelets. B-s...

Half-band filters are important for applications to multirate signal processing and wavelets. Previously, FIR half-band filters have mainly been treated. However, it should be recognized that the IIR filter can produce frequency characteristics similar to those of the FIR filter with a low order. Also, in the applications of filter banks and wavelets, design of a half-band filter is needed in w...

We explore the ramifications of using wavelet compression on turbulent-flow data from scientific simulations. As upcoming I/O constraints may significantly hamper the ability of scientific simulations to write full-resolution data to disk, we feel this study enhances the understanding of exascale science with respect to potentially applying wavelets in situ. Our approach repeats existing analys...

We present opt imized b iorthogonal and orthonormal wavelets for embedded zerotree wavelet compression of fingerprint images. These were obtained by simulated annealing over the wavelet filter coefficients using rms error between original and recovered images as the cost to be minimized. Linear-phase biorthogonal wavelets optimized for fingerprint image compression provide significantly improve...

This paper proposes a learning algorithm for the random field models whose energy functions are in the form of linear combinations of rectified filter responses from subsets of wavelets selected from a given over-complete dictionary. The algorithm consists of the following two components. (1) We propose to induce the wavelets into the random field model by a generative version of the epsilon-bo...

A wave is usually defined as an oscillating function that is localized in both time and frequency. A wavelet is a “small wave”, which has its energy concentrated in time providing a tool for the analysis of transient, non-stationary, or time-varying phenomena [1, 2]. Wavelets have the ability to allow simultaneous time and frequency analysis via a flexible mathematical foun‐ dation. Wavelets ar...

2D wavelets are usually generated from 1D wavelets through the rectangular or through the square decomposition scheme. In this paper a new adaptive 2D decomposition scheme for compression related applications is presented. The adaptive 2D decomposition selects 2D wavelet functions based on the compression of the coefficients, but needs only the same number of 1D filter operations as the rectang...

We propose a new approach to improve the performance of speech enhancement techniques based on wavelet thresholding. First, space–adaptation of the threshold is obtained by extending the principle of the level–dependent threshold to the Wavelet Packet Transform (WPT). Next, the time–adaptation is introduced using the Teager Energy Operator (TEO) of the wavelets coefficients. Finally, the time–s...