Results 161 to 170 of about 656,594 (178)

EEG Ocular Artefacts and Noise Removal

2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007
The general framework of this research is the pre-processing of the electroencephalographic (EEG) signals. The goal of this paper is to compare several combinations of wavelet denoising (WD) and independent component analysis (ICA) algorithms for noise and artefacts removal. These methods are tested on simulated EEG, using different evaluation criteria.
Didier Maquin, Rebeca Romo-Vázquez, Radu Ranta, Valérie Louis-Dorr   +3 more
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Fuzzy Transforms in Removing Noise

2006
The technique of fuzzy transform (F-transform for short) has been introduced in [6, 5]. It consists of two phases: direct and inverse. We have proved that the inverse F-transform has good approximation properties and is very simple to use.
Irina Perfilieva, Radek Valasek
openaire   +2 more sources

SNORE: spike noise removal and detection

IEEE Transactions on Medical Imaging, 1994
A method for detection and removal of random spike noise in magnetic resonance (MR) raw data (k-space data) is described. This method would reduce or eliminate the corduroy-type and higher than usual level artifacts in MR images resulting from random spike noise in k-space data. The method described involves applying a spatially varying threshold to be
T.K.F. Foo, J.D. Mitchell, N.S. Grigsby, B.E. Slayman   +3 more
openaire   +2 more sources

A Learning Filter for Removing Noise Interference

IEEE Transactions on Biomedical Engineering, 1983
We have developed a microcomputer-based filter that removes line induced electrical interference from biopotential signals by learning one period of the noise waveform and subtracting it from the signal. Since it uses a noise template, the filter can remove noise waveforms containing several harmonics of the 60 Hz line frequency.
Willis J. Tompkins, Gregory S. Furno
openaire   +3 more sources

Nonparametric Impulsive Noise Removal

2004
In this paper a novel 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 in a sliding filter window. The obtained results show good noise removal capabilities and excellent structure preserving properties of the
Rastislav Lukac, B. Smolka
openaire   +2 more sources

Notice of Removal Low-frequency image noise removal using white noise filter

2016 IEEE International Conference on Image Processing (ICIP), 2016
Image noise filters usually assume noise as white Gaussian. However, in a capturing pipeline, noise often becomes spatially correlated due to in-camera processing that aims to suppress the noise and increase the compression rate. Mostly, only high-frequency noise components are suppressed since the image signal is more likely to appear in the low ...
Meisam Rakhshanfar, Maria A. Amer
openaire   +2 more sources

Fuzzy Filters for Noise Removal

2003
An image may be subject to noise from several sources. The presence of noise in an image can affect the accuracy of the results considerably. Because of its wide applicability to image filtering, several fuzzy filter methods have been proposed. In this chapter, a survey of different design techniques for fuzzy filters is presented.
Leonardo Javier Delgado-Rangel, Manuel Guillermo Forero-Vargas   +1 more
openaire   +2 more sources

A study on impulse noise removal for varied noise densities

Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India, 2010
Digital images are generally affected by noise due to acquisition process or by transmission process. Most of the images are assumed to have variety of noise. Different algorithms are used depending on the noise model. Number of algorithms have been developed in the past years to denoise the images. In this paper different existing denoising algorithms
Padmavathi Ganapathi, V. Radhika
openaire   +2 more sources

Connected filters for noise removal

[1988 Proceedings] 9th International Conference on Pattern Recognition, 2003
A class of filters for edge-preserving noise removal is presented. The basic idea is that to retain connectedness in the filter, the new pixel value is calculated from the values in a local, connected area. The method described is related to the well-known KNN (k-nearest neighbors) method.
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Switching bilateral filter with a texture/noise detector for universal noise removal

2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010
In this paper, we propose a switching bilateral filter (SBF) with a texture and noise detector for universal noise removal. Operation was carried out in two stages: detection followed by filtering. For detection, we propose the sorted quadrant median vector (SQMV) scheme, which includes important features such as edge or texture information.
Chih Hsing Lin, Ching-Te Chiu, Jia Shiuan Tsai   +2 more
openaire   +4 more sources