Power system fault identification using information conveyed by the wavelet analysis of power system transients is proposed for detecting types of transmission line faults. In this paper, a comparative study of wavelet based de-noising signal based on wavelet thresholding is proposed. Discrete Wavelet Transform (DWT) analysis of the transient disturbance caused as a result of occurrence some of...

Dual tree complex wavelet transform(DTCWT) is a form of discrete wavelet transform, which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. The purposes of de-noising are reducing noise level and improving signal to noise ratio (SNR) without distorting the signal or image. This paper proposes a method for removing white Gaussian noi...

Local adaptive image de-noising in transform domain is a powerfull tool for adapting to unknown smoothness of the images. In this work we propose to perform local adaptive denoising with adaptively varying local transform support size rather than using a transform with ¿xed size. We use a special rule (Intersection of Con¿dence Intervals ICI) to select the optimum window sizes locally. The algo...

We address the problem of online de-noising a stream of input points. We assume that the clean data is embedded in a linear subspace. We present two online algorithms for tracking subspaces and, as a consequence, de-noising. We also describe two regularization schemas which improve the resistance to noise. We analyze the algorithms in the loss bound model, and specify some of their properties. ...

As many traditional de-noising methods fail in the intensive noises environment and are unadaptable in various noisy environments, a method of speech enhancement has been advanced based on dynamic Fractional Fourier Transform (FRFT)filtering. The acoustic signals are framed. The renewing methods are put in FRFT optimal disperse degree of noising speech and this method is implemented in detail. ...

We proposed a technique to detect the global addition of noise to a digital image. As an anti-forensics tool, noise addition is typically used to disguise the visual traces of image tampering or to remove the statistical artifacts left behind by other operations. As such, the blind detection of noise addition has become imperative as well as beneficial to authenticate the image content and reco...

A noiseless ECG identification technology is an emerging new biometric modality. Different techniques for de-noising of ECG signal are prevalent in recent literatures such as Particle Filter (PF), wavelet transforms (WT), Empirical Mode Decomposition (EMD) & Ensemble-EMD Method. In view of the fact that Analysis of ECG signals becomes difficult to inspect the cardiac activity in the presence of...

˗Image de-noising is an important challenging issue in image pre-processing. Two popular methods to the problem are partial differential equation (PDE) based nonlinear diffusion method and singular value decomposition (SVD) method. Various image de-noising algorithms based on these two methods have been independently developed. This paper proposes an approach for image de-noising by performing ...

The widely used Total Variation de-noising algorithm can preserve sharp edge, while removing noise. However, since fixed regularization parameter over entire image, small details and textures are often lost in the process. In this paper, we propose a modified Total Variation algorithm to better preserve smaller-scaled features. This is done by allowing an adaptive regularization parameter to co...