The classification of transient timevarying electroencephalography (EEG) is quite important for further understanding the brain function. In order to classify different kinds of nonstationary EEG rhythms, wavelet packet analysis is used for designing sub-band filters with specified band-passed characteristics. Four kinds of wavelet packet decomposition using Daubechies wavelet are employed to i...

Compressing an image is significantly different than compressing raw binary data. Of course, general purpose compression programs can be used to compress images, but the result is less than optimal. The compression is achieved by many algorithms like Haar, EZW, JPEG2000 and SPIHT [4] and we can get some good results but more efficient algorithm is required which is necessary to improve the PSNR...

ABSTRACT: This paper investigates how different aspects of the wavelet transform, such as the selection of a particular wavelet filter and choosing between the decimated and undecimated version of the decomposition scheme, affect the overall performance of satellite image fusion. Using data, which were acquired in the visible and near infrared wavelength spectrum, experiments were carried out, ...

This paper proposes a blind reversible watermarking techniquewhich incorporates the histogram shifting in wavelet domain. The integer wavelet transform is used to transform the image into wavelet domain. The watermark data is embedded into the sub-band coefficients identified by just noticeable distortion (JND)of the transformed host image. To ensure the prohibition of pixel overflow and underf...

This article presents a computationally tractable probabilistic model for the relation between the complex wavelet coefficients of two images of the same scene. The two images are acquisitioned at distinct moments of times, or from distinct viewpoints, or by distinct sensors. By means of the introduced probabilistic model, we argue that the similarity between the two images is controlled not by...

tion Classifica ject Sub s Mathematic 2000 62M10, 62G05. Abstract This paper presents an alternative approach to wavelet smoothing procedure for a time series model of signal added to autocorrelated stationary errors. The aim is to estimate the signal globally with near minimum risk. The usual approach to this problem is to threshold the wavelet coefficients with different thresholds in each le...

In this paper we introduce a new public digital watermarking technique for video copyright protection working in the Discrete Wavelet Transform domain. The scheme uses binary images as watermarks. These are embedded in the detail wavelet coefficients of the middle Wavelet sub-bands. The method is a combination of spread spectrum and quantization based watermarking. Every bit of the watermark is...

This paper presents image compression with wavelet based method. The wavelet transformation divides image to lowand high pass filtered parts. The traditional JPEG compression technique requires lower computation power with feasible losses, when only compression is needed. However, there is obvious need for wavelet based methods in certain circumstances. The methods are intended to the applicati...

Spatial and/or temporal variabilities of clouds is of paramount importance for at least two intensely researched sub-problems in global and regional climate modeling: • cloud-radiation interaction where correlations can trigger three-dimensional (3D) radiative transfer effects; and • dynamical cloud modeling where the goal is to realistically reproduce the said correlations. We propose wavelets...

The image gets corrupted by Additive White Gaussian Noise during the process of acquisition, transmission, storage and retrieval. Denoising refers to suppressing the noise while retaining the edges and other important detailed structures as much as possible. This paper presents a general structure of the recovery of images using a combination of variation methods and wavelet analysis. The varia...