Finding a good wavelet for a particular application and type of input data is a difficult problem. Traditional methods of wavelet deus on abstract properties of the wavelet that ca...
When a host image is watermarked multiple times by the same algorithm collisions can occur. This makes it difficult for an image to host multiple watermarks. But this hosting is n...
In recent years wavelets were shown to be effective data synopses. We are concerned with the problem of finding efficiently wavelet synopses for massive data sets, in situations...
In the paper, we proposed a novel feature descriptor using over-complete wavelet transform and wavelet domain based fractal signature for texture image analysis and retrieval. Trad...
Multiresolution video denoising is becoming an increasingly popular research topic over recent years. Although several wavelet based algorithms reportedly outperform classical sing...
Mihajlo Katona, Aleksandra Pizurica, Nikola Teslic...
Several studies have demonstrated the effectiveness of Haar wavelets in reducing large amounts of data down to compact wavelet synopses that can be used to obtain fast, accurate a...
Antonios Deligiannakis, Minos N. Garofalakis, Nick...
This paper presents a wavelet neural-network for learning and approximation of chaotic time series. Wavelet-networks are inspired by both feed-forward neural networks and the theo...
Abstract. In this paper, we study the problem of restoring multicomponent images. In particular, we investigate the effects of accounting for the correlation between the image com...
A long horizon end-to-end delay forecast, if possible, will be a breakthrough in traffic engineering. This paper introduces a hybrid approach to forecast end-to-end delays using ...
In this paper, we present a novel algorithm for wavelet domain image denoising using the soft thresholding function. The thresholds are designed to be locally optimal with respect...
Sumohana S. Channappayya, Alan C. Bovik, Robert W....