The removal of noise from speech signals has applications ranging from speech enhancement for cellular communications, to front ends for speech recognition systems. Spectral techniques are commonly used in these applications, but frequently result in audible distortion of the signal. A nonlinear time-domain method called dual extended Kalman filtering (DEKF) is presented that demonstrates signi...

Modified progressive switching median filter is proposed. It is constructed using introduction of the impulse noise detector from adaptive switching median filter into the progressive switching median filter. The results of comparative analysis of new algorithm with other filters are presented. The results show that the proposed algorithm is more efficient in the case of randomvalued impulse no...

This paper focuses on generalized weighted vector filters which constitute a powerful filtering frameworkfor multichannel signalprocessing.The utilization of a generalized multichannel sigmoidal adaptation scheme allows to accommodate the filter parameters to varying signal and noise statistics. Experimental results indicate that the presented multichannel filters are capable of removing impuls...

A method for designing lifting dyadic wavelet filters with vanishing moments is proposed. The method is applied for constructing spline dyadic wavelet filters with vanishing moments. The constructed filters are used together with a threshold masking technique for removing Gaussian noise from noise corrupted images.

Image noise removal is most important pre-processing step of image processing. Filtering method is emphasized for all types of de-noising schemes used for noise removal. In this paper, we have study about the different methods based on non-linear filter to remove the impulse noise from images. Different image noise removal algorithms are studied and some parameters are compared in a wide range ...

Noise reduction for speech signals has applications ranging from speech enhancement for cellular communications, to front ends for speech recognition systems. A neural network based time-domain method called Dual Extended Kalman Filtering (Dual EKF) is presented for removing nonstationary and colored noise from speech. This paperdescribes the algorithm and provides a set of experimental results.

Morphological filters based on the composition of openings and closings called alternating sequential filters are examined and their noise suppression action is investigated. Also they are compared with conventional filters then from the results it is found that alternating sequential filters are better than these filters in impulse noise removing.

Abstract Efficiency of noise removing algorithms depends on two main parameters first one is how accurately it identify the noisy pixels and second one is how much accurately it calculate the replacing value for noisy pixels. This Paper presents highly efficient algorithm to detect impulse noise (salt and pepper) up to 99% of noise ratio. Experimental results shows efficiency of algorithm is mo...

We report a reduction of the frequency noise in coplanar waveguide superconducting resonators. The reduction of 7 dB is achieved by removing the exposed dielectric substrate surface from the region with high electric fields and by using NbTiN. In a model-analysis the surface of NbTiN is found to be a negligible source of noise, experimentally supported by a comparison with NbTiN on SiOx resonat...

In this research, surface electromyography (SEMG) signal analysis from the right rectus femoris muscle is performed during walk. Wavelet transform (WT) has been applied for removing noise from the surface SEMG. Gaussianity tests are conducted to understand changes in muscle contraction and to quantify the effectiveness of the noise removal process. Results show that the proposed method can effe...