ECG signal and generally biomedical signals change their statistical properties over time. Researchers can use multiresolution techniques for analyzing non-stationary signals. Traditional analysis techniques like fourier transform and short time fourier Transform are confined to stationary signals only. Multiresolution techniques like Wavelet transform is a powerful instrument in catching zerod...

In this paper, the authors conduct a review on redundant wavelet transform (RDWT) in video signal processing. As an over-complete version of discrete wavelet transform (DWT), RDWT provides several advantages over the traditional DWT. In video coding area, we utilize its shift-invariant property and its phase-diverse multihypothesis, which are not provided by DWT, to build high performance video...

In this paper, we present a Stationary Wavelet Transform (SWT) based method for the purpose of despeckling the Synthetic Aperture radar (SAR) images by applying a maximum a posteriori probability (MAP) condition to estimate the noise free wavelet coefficients. The solution of the MAP estimator is based on the assumption that the wavelet coefficients have a known distribution. Rayleigh distribut...

in this paper we present a method to perform flood frequency analysis (ffa) when the assumption of stationary is not important (or not valid). a wavelet transform model is developed to ffa. a full series is applied to ffa using two different wavelet functions, and then a combined method is investigated. in the combined method, all discharge data which were less than the lowest value of annual m...

In this correspondence, an image resolution enhancement technique based on interpolation of the high frequency subband images obtained by discrete wavelet transform (DWT), stationary wavelet transform (SWT) and the input image has been proposed. The image quality has been enhanced by incorporating stationary wavelet transform (SWT). DWT decomposes an input image into four subbands. Out of these...

Fourier Transform and its tools have been applied popularly in many engineering applications. However, the Fourier Transform cannot analyze non-stationary, non-linear and intermittent signals with simultaneously time-frequency plane. Wavelet Transform have been invented recently to cope with limitations of the Fourier Transforms. This paper presents Continuous Wavelet Transform and its recent a...

0957-4174/$ see front matter 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.eswa.2013.12.027 ⇑ Corresponding author. Tel.: +91 416 2202364; fax: +91 416 2243092. E-mail addresses: [email protected] (M. Monica Subashini), sksahoo@ vit.ac.in (S.K. Sahoo). 1 Tel.: +91 416 2202467; fax: +91 416 2243092. 2 Abbreviations used: PCNN, pulse coupled neural networks; ICM, i...

ABSTIUCT In our previous work, we introduced a new class of nonstationary stochastic processes whose spectral representation is associated with the wavelet transforms and established a mathematical framework for the analysis of such processes 111. We refer to these processes as uffine stptionary processes. These processes are indexed by the affine p u p , or ax+b group, which can be though of a...

In recent years, wavelet based algorithms have been successful in different signal processing tasks. The wavelet transform is a powerful tool because it manages to represent both transient and stationary behaviours of a signal with few transform coefficients. In this paper we present new expansions and algorithms which improve wavelet algorithms. First we focus on one dimensional piecewise smoo...

46 Denoising EOG Signal using Stationary Wavelet Transform Naga Rajesh A, Chandralingam S, Anjaneyulu T, Satyanarayana K Department of Physics, Jawaharlal Nehru Technological University Hyderabad, Hyderabad-3, India, [email protected] Department of Electrical Engineering, IIT Bombay, India, [email protected] Department of Biomedical Engineering, Osmania University, Hyderabad...