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Impulse noise

About: Impulse noise is a research topic. Over the lifetime, 4816 publications have been published within this topic receiving 63970 citations.


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Journal ArticleDOI
TL;DR: The proposed method showed promising results and high noise robustness to a wide range of heart sounds, however, more tests are needed to address any bias that may have been introduced by different sources of heartSounds in the current training set, and to concretely validate the method.
Abstract: A new framework for heart sound analysis is proposed. One of the most difficult processes in heart sound analysis is segmentation, due to interference form murmurs. Equal number of cardiac cycles were extracted from heart sounds with different heart rates using information from envelopes of autocorrelation functions without the need to label individual fundamental heart sounds (FHS). The complete method consists of envelope detection, calculation of cardiac cycle lengths using auto-correlation of envelope signals, features extraction using discrete wavelet transform, principal component analysis, and classification using neural network bagging predictors. The proposed method was tested on a set of heart sounds obtained from several on-line databases and recorded with an electronic stethoscope. Geometric mean was used as performance index. Average classification performance using ten-fold cross-validation was 0.92 for noise free case, 0.90 under white noise with 10 dB signal-to-noise ratio (SNR), and 0.90 under impulse noise up to 0.3 s duration. The proposed method showed promising results and high noise robustness to a wide range of heart sounds. However, more tests are needed to address any bias that may have been introduced by different sources of heart sounds in the current training set, and to concretely validate the method. Further work include building a new training set recorded from actual patients, then further evaluate the method based on this new training set.

98 citations

Journal ArticleDOI
TL;DR: Under the framework of switching median filtering, a highly effective algorithm for impulse noise detection is proposed aiming at providing solid basis for subsequent filtering and in principle simpler as it is intuitive and easy to implement as it has uncomplicated structure and few codes.
Abstract: Under the framework of switching median filtering, a highly effective algorithm for impulse noise detection is proposed aiming at providing solid basis for subsequent filtering. This algorithm consists of two iterations to make the decision as accurate as possible. Two robust and reliable decision criteria are proposed for each iteration. Extensive simulation results show that the false alarm rate and miss detection rate of the proposed algorithm are both very low and substantially outperform existing state-of-the-art algorithms. At the same time, the proposed algorithm is in principle simpler as it is intuitive and it is easy to implement as it has uncomplicated structure and few codes.

98 citations

Posted Content
TL;DR: This paper attempts to undertake the study of three types of noise such as Salt and Pepper (SPN), Random variation Impulse Noise (RVIN), Speckle (SPKN) and they are compared with one another to choose the base method for removal of noise from remote sensing image.
Abstract: This paper attempts to undertake the study of three types of noise such as Salt and Pepper (SPN), Random variation Impulse Noise (RVIN), Speckle (SPKN). Different noise densities have been removed between 10% to 60% by using five types of filters as Mean Filter (MF), Adaptive Wiener Filter (AWF), Gaussian Filter (GF), Standard Median Filter (SMF) and Adaptive Median Filter (AMF). The same is applied to the Saturn remote sensing image and they are compared with one another. The comparative study is conducted with the help of Mean Square Errors (MSE) and PeakSignal to Noise Ratio (PSNR). So as to choose the base method for removal of noise from remote sensing image.

98 citations

Journal ArticleDOI
TL;DR: It is shown that, in the presence of impulse noise and except for systems operating at very high spectral efficiency, the IR of MC schemes is lower than that of SC schemes, whereas MC schemes are to be preferred for very high coding rates or in uncoded systems.
Abstract: In this paper, we investigate the ultimate performance limits, in terms of achievable information rate (IR), of communication systems impaired by impulse noise. We compare single carrier (SC) and multi-carrier (MC) transmission systems employing quadrature amplitude modulation (QAM) formats. More precisely, we consider SC schemes with coded modulations and MC systems based on orthogonal frequency division modulation (OFDM). For the MC schemes, we introduce a theoretically equivalent channel model which makes the computation of the IR feasible. This simple channel model will be referred to as interleaved MC. We show that, in the presence of impulse noise and except for systems operating at very high spectral efficiency, the IR of MC schemes is lower than that of SC schemes. More precisely, use of MC schemes may lead to an unavoidable fundamental loss with respect to SC schemes at typical coding rates, whereas MC schemes are to be preferred for very high coding rates or in uncoded systems. These results hold for additive white Gaussian noise (AWGN) and dispersive channels, either considering plain OFDM or MC schemes employing water-filling and bit-loading algorithms. In order to validate our theoretical results, we also obtain the bit error rate (BER) performance of SC and MC schemes through Monte Carlo simulations. A few trellis-coded modulation (TCM) and low-density parity-check (LDPC)-coded schemes are considered. The obtained SNR loss in the BER curves between the AWGN and impulse noise channels matches well with the corresponding IR gap.

97 citations

Book ChapterDOI
TL;DR: A unified variational approach to salt and pepper noise removal and image deblurring is presented, and elements from the Mumford-Shah functional, that favor piecewise smooth images with simple edge-sets, are used for regularization.
Abstract: The problem of image deblurring in the presence of salt and pepper noise is considered. Standard image deconvolution algorithms, that are designed for Gaussian noise, do not perform well in this case. Median type filtering is a common method for salt and pepper noise removal. Deblurring an image that has been preprocessed by median-type filtering is however difficult, due to the amplification (in the deconvolution stage) of median-induced distortion. A unified variational approach to salt and pepper noise removal and image deblurring is presented. An objective functional that represents the goals of deblurring, noise-robustness and compliance with the piecewise-smooth image model is formulated. A modified L1 data fidelity term integrates deblurring with robustness to outliers. Elements from the Mumford-Shah functional, that favor piecewise smooth images with simple edge-sets, are used for regularization. Promising experimental results are shown for several blur models.

97 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202371
2022168
2021111
2020175
2019206
2018210