A selective wavelet shrinkage algorithm for digital image denoising is presented. The performance of this method is an improvement upon other methods proposed in the literature and is algorithmically simple for large computational savings. The improved performance and computational speed of the proposed wavelet shrinkage algorithm is presented and experimentally compared with established method...

In this paper, we propose a new video denoising algorithm which uses an efficient wavelet based spatio-temporal filter. The filter first applies 2D discrete wavelet transform (DWT) in horizontal and vertical directions on an input noisy video frame and then applies 1-D discrete cosine transform (DCT) in the temporal direction in order to reduce the redundancies which exist among the wavelet coe...

this article presents an analytic approach to study admissibility conditions related to classical full wavelet systems over finite fields using tools from computational harmonic analysis and theoretical linear algebra. it is shown that for a large class of non-zero window signals (wavelets), the generated classical full wavelet systems constitute a frame whose canonical dual are classical full ...

In the total variation wavelet inpainting model, when the low-frequency wavelet coefficients and almost all high-frequency wavelet coefficients, in some areas, are all lost, the wavelet coefficients always can not be filled properly. Based on the defect, the curvature term is introduced into the model to guide the filling process, the Euler-Lagrange equation of the new model is derived through ...

This article introduces a systematic study for computational aspects of classical wavelet transforms over finite fields using tools from computational harmonic analysis and also theoretical linear algebra. We present a concrete formulation for the Frobenius norm of the classical wavelet transforms over finite fields. It is shown that each vector defined over a finite field can be represented as...

Wavelet shrinkage is an image denoising technique based on the concept of thresholding the wavelet coefficients. The key challenge of wavelet shrinkage is to find an appropriate threshold value, which is typically controlled by the signal variance. To tackle this challenge, a new image shrinkage approach, called AntShrink, is proposed in this paper. The proposed approach exploits the intra-scal...

The algorithm of wavelet decomposition and reconstruction are applied in the audio error concealment method in this paper. When there is lost frame of the audio signal, the correct frames which lie before and after the lost frame are wavelet decomposed firstly. Then the two sets of the wavelet coefficients obtained from the wavelet decomposition are utilized to get the wavelet coefficients for ...

The WaveStat project deals with the exploratory Cluster Analysis of picture data and wavelet-built coefficients. Cluster Analysis means to collect elements (i.e. pixels) of the same property (in this context this means: gray value) to a cluster. These clusters can be visualized by colorizing them or by reconstructing them to a grayscale picture. In this article we will show that a cluster analy...

In this paper we discuss a method for construction of algebraic wavelet coefficients, i.e., wavelet coefficients lying in an algebraic extension field of Q: The method relies on a strengthened version of a theorem due to L. FEJÉR and F. RIESZ. As an application, we prove that the Daubechies wavelets have algebraic wavelet coefficients. We show that there exist uncountably many transcendent scal...