To address sparse channel estimation problem in nonGaussian impulsive noise environment, a recursive maximum correntropy criteria (RMCC) algorithm using sparse constraint is proposed to combat impulsive-inducing instability. Specifically, the recursive algorithm on the correntrioy with a forgetting factor of error at iteration is to solve steady-state error for improving the maximum correntropy...

In this paper a novel method of noise reduction in color images is presented. The new technique is capable of attenuating both impulsive and Gaussian noise, while preserving and even enhancing the sharpness of the image edges. Extensive simulations reveal that the new method outperforms significantly the standard techniques widely used in multivariate signal processing. In this work we apply th...

In this paper, we introduce the Vector Rank M-type L (VRML)-filter to remove impulsive noise from color images and video sequences. The proposed filter uses the Median M-type (MM) and Ansari–Bradley– Siegel–Tukey M-type (AM) estimators into L-filter to provide robustness to proposed filtering scheme. We also introduce the use of impulsive noise detectors to improve the properties of noise suppr...

Abstract : In this paper a new class of filters designed for the removal of impulsive noise in color images is presented. The proposed filter class is based on the nonparametric estimation of the density probability function of pixels in a sliding filtering window. The comparison of the new filtering method with the standard techniques used for impulsive noise removal, indicates good noise remo...

Performance of an automatic speech recognition (ASR) system tends to be dramatically degraded in the presence of impulsive noise. In the previous work [1], we proposed flooring the observation probability (FOP) to compensate the adverse effect of impulsive noise on sensitive dimensions of Mel-frequency cepstral coefficient (MFCC) features. Linear prediction cepstral coefficient (LPCC) is anothe...

Impulsive Noise Cancellation in practice is a challenging task. In case of biomedical signals like ECG, EMG, EEG are even challenging for noise cancellation. These signals suffer from impulsive noise at the time of acquisition. In this paper, Cardiac signal corrupted with impulsive noise at the time of acquisition is considered. Different filtering algorithms are being applied to remove the noi...

The new stochastic approach of impulsive noise filtering, based on the input sample separation by modified clusterization criterion, is proposed. It is shown that preliminary filtration by the proposed procedure provides robust narrowband sound frequency estimation and eliminates failures of the estimation algorithm caused by the impulsive noise.

The Gaussian distribution is an inadequate description of certain types of real-life noise that display impulsive characteristics. The α-stable distribution has been suggested as a more appropriate model. Bilinear timefrequency representations (TFRs) and time-scale representations (TSRs) have been used to efficiently implement detectors of non-stationary signals in Gaussian noise. In this paper...

In this work, an approach to the problem of impulsive noise removal in gray scale images is presented. We describe two models of adaptive mathematical morphology that improve the classical mathematical morphology in the removal of impulsive noise. The proposed method adjust the structuring elements to the local context of the image. The comparison with classical mathematical morphology denoisin...

Abstrak –The objective of this paper is a new MeanMedian filtering for denoising extremely corrupted images by impulsive noise. Whenever an image is converted from one form to another, some of degradation occurs at the output. Improvement in the quality of these degraded images can be achieved by the application of Restoration and /or Enhancement techniques. Noise removing is one of the categor...