This paper proposes a cumulant (higher-order statistics) based mean-square-error (MSE) criterion for the design of Wiener filters when both the given wide-sense stationary random signal x(n) and the desired signal d(n) are non-Gaussian and contaminated by Gaussian noise sources. It is theoretically shown that the designed Wiener filter associated with the proposed criterion is identical to the ...

This contribution presents a variation of the Wiener filter criterion, i.e. minimizing the mean squared error, by combining it with the main principle of normalized convolution, i.e. the introduction of prior information in the filter process via the certainty map. Thus, we are able to optimize a filter according to the signal and noise characteristics while preserving edges in images. In spite...

We present three different sequential Wiener filters, namely, isotropic, orientation and anisotropic. The first one is similar to the classical Wiener filter in the sense that it uses an isotropic neighborhood to estimate its parameters. Here we present a sequential version of it. The orientation Wiener filter uses oriented neighborhoods to estimate the structure orientation present at each vox...

We present three different sequential Wiener filters, namely, isotropic, orientation and anisotropic. The first one is similar to the classical Wiener filter in the sense that it uses an isotropic neighborhood to estimate its parameters. Here we present a sequential version of it. The orientation Wiener filter uses oriented neighborhoods to estimate the structure orientation present at each vox...

The corruption of speech due to presence of additive background noise causes severe difficulties in various communication environments. This paper presents a novel noise reduction technique based upon a combination of cascaded spectral subtraction and Wiener filter methods in wavelet domain. The scheme’s performance is illustrated by experiments in a noisy car environment, in comparison with sp...

Removing noise from the original medical image is still a challenging research in image processing. This paper presents a new method for speckle noise reduction in Optical coherence Tomography (OCT). Stationary wavelet transform (SWT) is employed to provide effective representation of the noisy coefficients. Nonlinear Anisotropic filtering of the Details coefficients improves the denoising effi...

This work presents a novel approach to speech enhancement by exploiting the bimodality of speech and the correlation that exists between audio and visual speech features. For speech enhancement, a visually-derived Wiener filter is developed. This obtains clean speech statistics from visual features by modelling their joint density and making a maximum a posteriori estimate of clean audio from v...

In this study by using noise-free signal estimation the reduction of noise in the image is being proposed. The dyadic stationary wavelet transform is used for both the wiener filter and in estimating the noise free signal. Finding a suitable filter bank and choosing other parameters of the wiener filter with respect to obtained signalto-noise ratio (SNR) is our goal. Testing was being performed...

A method for improving the energy efficiency of OFDM systems based on differential transformation and extrapolation is considered. The possible structure of the extrapolator is analyzed, the implementation of an extrapolator based on the Kalman Bucy filter and the Wiener filter is considered. The results of carried out simulation confirming the effectiveness of the proposed scheme are given.

We investigate Wiener filtering of wavelet coefficients for signal denoising. Empirically designed wavelet-domain Wiener filters have superior performance over other denoising algorithms using wavelet thresholding. However, it is not clear how we should choose the signal model that is used to design the filter, because the effect of model selection on the filter performance was hard to understa...