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...

annihilation or reduction of each kind of noise blended in correct data signals is a field that has attracted many researchers. it is a fact that fuzzy theory presents full capability in this field. fuzzy filters are often strong in smoothing corrupted signals, whereas they have simple structures. in this paper, a new powerful yet simple fuzzy procedure is introduced for sharpness reduction in ...

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.

Autoregressive (AR) modeling is widely used in signal processing. The coefficients of an AR model can be easily obtained with a least mean square (LMS) prediction error filter. However, it is known that this filter gives a biased solution when the input signal is corrupted by white Gaussian noise. Treichler suggested the -LMS algorithm to remedy this problem and proved that the mean weight vect...

This frame work describes a computationally more efficient and adaptive threshold estimation method for image denoising in the wavelet domain based on Generalized Gaussian Distribution (GGD) modeling of subband coefficients. In this proposed method, the choice of the threshold estimation is carried out by analysing the statistical parameters of the wavelet subband coefficients like standard dev...

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...

We investigate a Wiener fusion method to optimally combine multiple estimates for the problem of image deblurring given a known blur and a corpus of sharper training images. Nearest-neighbor estimation of high frequency information from training images is fused with a standard Wiener deconvolution estimate. Results show an improvement in sharpness and decreased artifacts compared to either the ...

Image denoising is the manipulation of the image data to produce a visually high quality image. At present there are a variety of methods to remove noise from digital images. There are different types of filters like mean filter, median filter, bilateral filter, wiener filter etc. to remove a single type of noise such as salt and pepper noise, speckle noise, Gaussian noise etc. But if the image...

This paper presents some image processing techniques that can be used for radiographic image enhancement. Contrast enhancement, filtering, denoising, and interpolation processes are carried out in this paper. Contrast enhancement is carried out using adaptive histogram equalization. Filtering is carried out using median, Wiener, Lee, and Kuan filters. Wavelet and curvelet transforms are used fo...