Abstract—Correlation matrices are ubiquitous throughout signal processing, networking and in many areas of science [1][2][3]. However, our study of the literature found that there is limited research on the structure of the indices in correlation matrix of wavelet coefficients, and in the exploitation of that structure to improve its computational efficiency. This article seeks to make a contri...

This article compares results obtained in previous studies using time-frequency representations (Wigner-Ville, Choi-Williams and Parametric) and the wavelet transform with those obtained with wavelet packet functions to show new findings about their quality in the analysis of ECoG recordings in human intractable epilepsy: data from 21 patients have been analyzed and processed with four types of...

In this study, hybrid Particle Swarm Optimization (PSO)-based Wavelet Neural Network (WNN) for natural scene text extraction is presented. In our approach, wavelet transformation is done on the different current and the wavelet coefficients are obtained. The wavelet coefficients are given as inputs to the wavelet neural network trained by Particle Swarm Optimization (PSO-WNN). The final network...

In this paper, a new approach for content-based image indexing and retrieval is presented. The proposed method is based on a combination of multiresolution analysis and color correlation histogram of the image. According to the new algorithm, the wavelet coefficients of the image are computed first using Daubechies3 wavelet. Then, monodimensional color correlogram of the horizontal and vertical...

The de-noising is a challenging task in the field of signal and image processing. Any natural image corrupted by gussian noise can be de-noised using wavelet method. Wavelet-based image denoising is an important technique in the area of image noise reduction. Wavelets have their natural ability to represent images in a very sparse form which is the foundation of wavelet-based denoising through ...

The traditional continuous wavelet transform is plagued by the cone-ofinfluence, ie wavelets which extend past either end of a finite timeseries return transform coefficients which tend to decrease as more of the wavelet is truncated. These coefficients may be corrected simply by rescaling the remaining wavelet. The corrected wavelet transform displays no cone-of-influence and maintains reconst...

In this paper, an efficient error resilience scheme aiming to give priority protection to certain area such as region of interest (ROI) in frame based on Wyner-Ziv(WZ) coding for wavelet based video transmission is proposed. By utilizing additional WZ coding, all the corresponding wavelet coefficients related to ROI will be specially protected during transmission on error prone channel and even...

Wavelet denoising is a commonly used method in the field of image denoising algorithms, based on the analysis of the characteristics of estimated wavelet coefficients in the wavelet threshold denoising and the traditional soft threshold and hard threshold method, in the light of the discontinuity of hard threshold and fixed deviation of soft threshold, and non-differentiable of compromise algor...