The aim of this study was to remove the two principal noises which disturb the surface electromyography signal (Diaphragm). These signals are the electrocardiogram ECG artefact and the power line interference artefact. The algorithm proposed focuses on a new Lean Mean Square (LMS) Widrow adaptive structure. These structures require a reference signal that is correlated with the noise contaminat...

This paper presents an ontological intelligent agent to remove impulse noise from highly corrupted images. It contains an image noise ontology to represent the image noise knowledge for the agent, a fuzzy inference mechanism for noise detection and removal, and an intelligent learning process for automatically generating the fuzzy numbers of the agent. The working environment for the intelligen...

The electrocardiogram (ECG) signal is susceptible to noise and artifacts and it is essential to remove the noise in order to support any decision making for specialist and automatic heart disorder diagnosis systems. In this paper, the use of Particle Swarm Optimization Neural Network (PSONN) for automatically identifying the cutoff frequency of ECG signal for low-pass filtering is investigated....

The classical solution to the noise removal problem is the Wiener lter, which utilizes the second-order statistics of the Fourier decomposition. Subband decomposi-tions of natural images have signiicantly non-Gaussian higher-order point statistics; these statistics capture image properties that elude Fourier-based techniques. We develop a Bayesian estimator that is a natural extension of the Wi...

Dapeng Zhang Zhou Wang City University of Hong Kong Department of Computer Science Kowloon, Hong Kong China E-mail: [email protected] Abstract. A novel filtering algorithm is presented to restore images corrupted by impulsive noise. As a preprocessing procedure of the noise cancellation filter, an improved impulse detector is used to generate a binary flag image, which gives each pixel a f...

An advanced non-linear cascading filter algorithm for the removal of high density salt and pepper noise from the digital images is proposed. The proposed method consists of two stages. The first stage Decision base Median Filter (DMF) acts as the preliminary noise removal algorithm. The second stage is either Modified Decision Base Partial Trimmed Global Mean Filter (MDBPTGMF) or Modified Decis...

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...

Noise attenuation by prediction filtering breaks down in the presence of high-amplitude noise when the prediction filter is corrupted by noise and the filter response to the noise overwhelms the signal. Spurious events are generated and the amplitude of the signal is reduced by prediction filtering under these circumstances. To reduce these undesired effects, the separation of signal and noise ...

A robust modeling approach is applied to remove speckle noise in synthetic aperture images. Conventional adaptive filtering approaches in speckle filtering smoothes the image selectively depending on the details of underlying textures, and tend to blur details after speckle removal. In the proposed approach, the image is assumed to be composed of structural and stochastic components, and the st...