Showing papers on "Impulse noise published in 2005"

Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

Abstract: This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise (noise candidates). In the second phase, the image is restored using a specialized regularization method that applies only to those selected noise candidates. In terms of edge preservation and noise suppression, our restored images show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only. Our scheme can remove salt-and-pepper-noise with a noise level as high as 90%.

A universal noise removal algorithm with an impulse detector

Abstract: We introduce a local image statistic for identifying noise pixels in images corrupted with impulse noise of random values. The statistical values quantify how different in intensity the particular pixels are from their most similar neighbors. We continue to demonstrate how this statistic may be incorporated into a filter designed to remove additive Gaussian noise. The result is a new filter capable of reducing both Gaussian and impulse noises from noisy images effectively, which performs remarkably well, both in terms of quantitative measures of signal restoration and qualitative judgements of image quality. Our approach is extended to automatically remove any mix of Gaussian and impulse noise.

Performance analysis of OFDM systems for broadband power line communications under impulsive noise and multipath effects

Abstract: The impulsive noise and multipath effects are the main reasons to cause bit errors in power line communications. In this paper, the bit error rate (BER) performance of the orthogonal frequency division multiplexing (OFDM) system under the impulsive noise and multipath effects are theoretically analyzed in terms of closed form formulas. Through the analysis, it is shown that OFDM can mitigate the adverse effect of the impulsive noise and only the heavily disturbed impulsive noise will interfere the BER performance of the OFDM system. It is also shown that the adverse effect of multipath is more serious than that of impulsive noise. In this paper, the guard interval is used to improve the BER performance of the OFDM system. As the longer guard interval is inefficient in using the signal power, the optimum guard interval that can achieve the best BER performance is studied.

Noise and health.

Abstract: Noise affects everybody in everyday life—at home, at leisure, during sleep, when traveling, and at work. However, human organisms are not prepared to shut off the noise. Hearing is a permanent process using cortical and subcortical structures to filter and interpret acoustical information; the analysis of acoustical signals is essential for human survival and communication. Noise is detrimental to health in several respects, for example, hearing impairment, sleep disturbance, cardiovascular effects, psychophysiologic effects, psychiatric symptoms, and fetal development (Stansfeld et al. 2000). Furthermore, noise has widespread psychosocial effects including noise annoyance, reduced performance, and increased aggressive behavior [American Academy of Pediatrics 1997; World Health Organization (WHO) 2001]. Noise causes acute mechanical damage to hair cells of the cochlea in the inner ear when the short-term sound intensity or peak impulse noise levels are very high {LAF (A-weighted sound pressure level) > 120 dB; LCpk (C-weighted peak sound pressure level) > 135 A-weighted decibels [dB(A)]}. In the long run, average sound pressure levels (LAeq) of > 85 dB(A) are likely to cause significant hearing loss due to metabolic exhaustion [International Organization for Standardization (ISO) 1990]. This is not only relevant in occupational settings but also with respect to leisure activities, including firecrackers, toy pistols, and other noisy toys; loud music in discotheques, concerts, and when listening via headphones; and noisy machines and tools (Maassen et al. 2001). Particularly, children and adolescents are affected (Bistrup et al. 2001). The WHO and the U.S. Environmental Protection Agency consider a daily average sound exposure equivalent to LAeq = 70 dB(A) to be safe for the ear (WHO 2000). The large numbers of young people with hearing impairments should serve as a warning. “Noise hygiene” can be improved, particularly through education at school. Even ear-safe sound levels can cause nonauditory health effects if they chronically interfere with recreational activities such as sleep and relaxation, if they disturb communication and speech intelligibility, or if they interfere with mental tasks that require a high degree of attention and concentration (Evans and Lepore 1993). The signal–noise ratio (in terms of signal processing) should be at least 10 dB(A) to ensure undisturbed communication. High levels of classroom noise have been shown to affect cognitive performance (Bistrup et al. 2001). Reading and memory have been reported to be impaired in schoolchildren who were exposed to high levels of aircraft noise (Hygge et al. 2002). Some studies have shown higher stress hormone levels and higher mean blood pressure readings in children exposed to high levels of community noise (Babisch 2000; Passchier-Vermeer 2000). During sleep, electrophysiologic awakening reactions can be detected in an electroencephalogram for event-related maximum noise levels above LAF = 40–45 dB(A) in the bedroom (e.g., aircraft overflights). Recent studies suggest even lower thresholds. The long-term somatic consequences of such arousals are still a matter of discussion and research (WHO Regional Office for Europe 2004). Sleep deprivation, however, is associated with an increased risk of accidents and injuries. Cardiovascular responses found during sleep were independent of sleep disturbance. A subject may sleep during relatively high noise levels but still show autonomic responses. Among other nonauditory health end points, short-term changes in circulation (including blood pressure, heart rate, cardiac output, and vasoconstriction) as well as in levels of stress hormones (including epinephrine, norepinephrine, and corticosteroids) have been studied in experimental settings for many years (Babisch 2003; Berglund and Lindvall 1995). From this, the hypothesis emerged that persistent noise stress increases the risk of cardiovascular disorders including high blood pressure and ischemic heart disease. Classical biologic risk factors have been shown to be elevated in subjects who were exposed to high levels of traffic noise. Nowadays the biological plausibility of the association is established (Babisch 2002). Its rationale is the general stress concept: Sound/noise is a psychosocial stressor that activates the sympathetic and endocrine systems. Acute noise effects do not occur only at high sound levels in occupational settings, but also at relatively low environmental sound levels when, more importantly, certain activities such as concentration, relaxation, or sleep are disturbed. The following questions need to be answered: Do these changes observed in the laboratory habituate, or do they persist under chronic noise exposure? If they habituate, what are the physiologic costs; if they persist, what are the long-term health effects? There is no longer any need to prove the noise hypothesis as such. Decision making and risk management rely on quantitative risk assessment, but not all biologically notifiable effects are of clinical relevance. The results of epidemiologic noise studies suggest an increase in cardiovascular risk with increasing noise exposure (e.g., Babisch 2000). Unfortunately, most of the individual studies that have been carried out lack statistical power. Over the years the quality of studies has improved, and many potential confounding factors have been considered. Some expert groups have rated the evidence of an association as sufficient (overview by Babisch 2002; Passchier-Vermeer 2003). Transportation noise from road and air traffic is the predominant sound source in our communities; outdoor sound levels for day–evening–night (Lden) > 65–70 dB(A) were found to be associated with odds ratios of 1.2–1.8 in exposed subjects compared with unexposed subjects [< 55–60 dB(A)] (Babisch 2000). Because large parts of the population are exposed to such noise levels [European Environmental Agency (EEA) 2004], noise policy can have a significant impact on public health (Kempen et al. 2002; Neus and Boikat 2000). For noise levels below an Lden of 55 dB(A), no major annoyance reactions or adverse health effects are to be expected. Studies use magnitude of effect, dose–response relationship, biological plausibility, and consistency of findings among studies as issues in epidemiologic reasoning. Environmental and health policy must determine acceptable noise standards that consider the whole spectrum from subjective well-being to somatic health. This means that limit values may vary depending on the severity of outcomes. Future noise research should focus on source-specific differences in risk characterization, combined effects, differences between objective (sound level) and subjective (annoyance) exposure on health, sensitive/vulnerable groups, sensitive periods of the day, coping styles, and other effect-modifying factors.

Nonlinear system identification in impulsive environments

Abstract: Nonlinear system identification has been studied under the assumption that the noise has finite second and higher order statistics. In many practical applications, impulsive measurement noise severely weakens the effectiveness of conventional methods. In this paper, /spl alpha/-stable noise is used as a noise model. In such case, the minimum mean square error (MMSE) criterion is no longer an appropriate metric for estimation error due to the lack of finite second-order statistics of the noise. Therefore, we adopt minimum dispersion criterion, which in turn leads to the adaptive least mean pth power (LMP) algorithm. It is shown that the LMP algorithm under the /spl alpha/-stable noise model converges as long as the step size satisfies certain conditions. The effect of p on the performance is also investigated. Compared with conventional methods, the proposed method is more robust to impulsive noise and has better performance.

Impulsive noise cancellation in multicarrier transmission

Abstract: A parallel between Reed-Solomon codes in the complex field and multicarrier transmission using orthogonal frequency-division multiplexing (OFDM) is first presented. This shows that when the signal is sent over some channel composed of Gaussian plus impulsive noise, the impulsive noise can be removed by a procedure similar to channel decoding, using information carried by the "syndrome." This result is first derived in a simple situation (oversampled discrete multitone, additive channel), which is merely of theoretical interest. In any case, consecutive zeros, in the output of the OFDM modulator, do not correspond to real subcarriers. Pilot tones are transmitted for synchronization or channel-estimation purposes. These pilot tones are generally scattered among the information ones. Our approach is to use these pilot tones as syndromes, in order to correct impulsive noise. We show that the correction capacity is conditioned by the position of these pilot tones in the transmitted sequence. A protection subsystem based on hypotheses tests is introduced after the decoding operation in order to detect malfunctions of this decoder. The efficiency of this technique is corroborated with simulations in the slightly modified Hiperlan2 context. Other extensions are then provided in order to increase the practical usefulness of the method.

Image deblurring in the presence of salt-and-pepper noise

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.

A decoding for low density parity check codes over impulsive noise channels

Abstract: Power line channel often suffers from impulsive interference generated by electrical appliances. Therefore, power line communication makes degradation due to such impulsive interference. We introduce Middleton's class a noise model into a statistical model of impulsive noise environment. In this paper, we apply LDPC (low density parity check) codes and sum-product decoding to additive white class a noise (AWAN) channels. We propose a sum-product decoding which is suitable for AWAN channels. In addition, we show the BER (bit error rate) performance of the proposed sum-product decoding in class a noise environment by computer simulation.

Impulsive noise removal using threshold Boolean filtering based on the impulse detecting functions

Abstract: A filter for impulsive noise removal is presented here. The problem of impulsive noise elimination is closely connected with the problem of maximal preservation of image edges. To avoid smoothing of the image during filtering, all noisy pixels must be detected. We consider here an approach, which is based on threshold Boolean filtering, where the binary slices of an image, obtained by the threshold decomposition, are processed by the impulse-detecting Boolean functions proposed. These functions provide a possibility of single-pass filtering, because they detect and replace impulses at the same time.

A New Efficient Impulse Detection Algorithm for the Removal of Impulse Noise

Abstract: A new impulse noise detection algorithm is presented, which can successfully remove impulse noise from corrupted images while preserving image details. The impulse detection algorithm is combined with median filtering to achieve noise removal. The main advantage of the proposed algorithm is that it can detect the impulse noise with high accuracy while reducing the probability of detecting image details as impulses. Also, it can be applied iteratively to improve the quality of restored images. It is efficient and low in complexity. Furthermore, it requires no previous training. Extensive experimental results show that the proposed approach significantly outperforms many well-known techniques.

On diversity reception over fading channels with impulsive noise

Abstract: In this paper, we analyze the performance of different diversity combining techniques over fading channels with impulsive noise. We use Middleton's Class A model for the noise distribution and adopt two noise models, which assume dependent and independent noise components on each branch. We systematically analyze the performance of maximum ratio combing (MRC), equal gain combining (EGC), selection combining (SC), and post-detection combining (PDC) under these impulsive noise models, and derive insightful lower and upper bounds. We show that even under impulsive noise, the diversity order is retained for each combining scheme. However, we also show that under both models, there is a fundamental tradeoff between diversity gain and coding gain. Under the independent noise model, PDC is shown to combat impulsive noise more effectively than MRC, EGC, and SC. Our simulation results also corroborate our analysis.

Oversampled filter banks as error correcting codes: theory and impulse noise correction

Abstract: Oversampled filter banks (OFBs) provide an overcomplete representation of their input signal. This paper describes how OFBs can be considered as error-correcting codes acting on real or complex sequences, very much like classical binary convolutional codes act on binary sequences. The structured redundancy introduced by OFBs in subband signals can be used to increase robustness to noise. In this paper, we define the notions of code subspace, syndrome, and parity-check polynomial matrix for OFBs. Furthermore, we derive generic expressions for projection-based decoding, suitable for the case when a simple second-order model completely characterizes the noise incurred by subband signals. We also develop a nonlinear hypotheses-test based decoding algorithm for the case when the noise in subbands is constituted by a Gaussian background noise and impulsive errors (a model that adequately describes the action of both quantization noise and transmission errors). Simulation results show that the algorithm effectively removes the effect of impulsive errors occurring with a probability of 10/sup -3/.

Iterative multidimensional impulse detectors for communications based on the classical diagnostic methods

Abstract: This letter introduces diagnostic impulse-detection methods in general, and, based on those, presents three iterative impulse detectors for communication receivers with an antenna array. These detectors are implemented either in a backward or forward search mode. The forward methods are shown to perform better. They can detect all the impulses, even though 90% of all the samples are corrupted.

Seamless change of depth of a general convolutional interleaver during transmission without loss of data

Abstract: Methods and communication systems are presented, in which impulse noise is monitored on a communication channel, and an interleaver depth is adjusted according to the monitored impulse noise without interrupting communication service.

An intelligent image agent based on soft-computing techniques for color image processing

Abstract: An intelligent image agent based on soft-computing techniques for color image processing is proposed in this paper. The intelligent image agent consists of a parallel fuzzy composition mechanism, a fuzzy mean related matrix process and a fuzzy adjustment process to remove impulse noise from highly corrupted images. The fuzzy mechanism embedded in the filter aims at removing impulse noise without destroying fine details and textures. A learning method based on the genetic algorithm is adopted to adjust the parameters of the filter from a set of training data. By the experimental results, the intelligent image agent achieves better performance than the state-of-the-art filters based on the criteria of Peak-Signal-to-Noise-Ratio (PSNR) and Mean-Absolute-Error (MAE). On the subjective evaluation of those filtered images, the intelligent image agent also results in a higher quality of global restoration.

Power Quality Disturbance Detection Based on Mathematical Morphology and Fractal Technique

Abstract: Based on mathematical morphology and grille fractal, a novel approach on power quality disturbance detection and location is presented in this paper. At first a parallel composite morphological filter with multiple-structure elements is designed to filter the random noise and impulse noise in power quality disturbance signals. Then to the filtered curves, an easy implementation criterion for singularity detection based on the change regularity of grille fractal is proposed to locate the start and end time that disturbance occurs. The voltage sag, swell, harmonic and their combined disturbances are used to verify the validity of the proposed filter-location approach. Numerical results show that the proposed approach is valid and effective

Image denoising using adaptive switching median filter

Abstract: A new adaptive switching median filter is proposed to remove salt-and-pepper impulse noise from corrupted image. The algorithm is developed by combining advantages of the known median-type filters with impulse noise detection step. Comparison of the given method with traditional filters is provided. A visual example is given to demonstrate the performance of the proposed filter.

Low-density parity-check coding for impulse noise correction on power-line channels

Abstract: This paper considers the design of near capacity-achieving error correcting codes for a discrete multi-tone system in the presence of both additive white Gaussian noise and impulse noise. Impulse noise is one of the main channel impairments in the power-line channel. One way to combat impulse noise is to detect the presence of the impulses and to declare an erasure when an impulse occurs. In this paper, we propose a coding system based on irregular low-density parity-check (LDPC) codes and bit-interleaved coded modulation. We show that by carefully choosing the degree distribution of the irregular LDPC code, both the additive noise and the erasures can be handled in a single code. We show that the proposed system can perform close to the capacity of the channel and for the same redundancy is significantly more immune to the impulse noise than the existing methods based on an outer Reed-Solomon code.

Robust and high-bit rate communications over PLC channels: a bit-loading multi-carrier spread-spectrum solution

Abstract: In this paper, we present a finite-granularity loading algorithm for multicarrier spread-spectrum modulation systems. The proposed scheme attempts to give a robust solution to the power line communication challenging task. Throughout the paper, the particular case of an adapted version of multi-carrier code-division-multiple-access (MC-CDMA) is considered, which is currently called spread-spectrum multicarrier multiple-access (SS-MC-MA). The presented algorithm assigns subcarriers, spreading codes, bits and energy per code to each user of the network in order to maximize the minimum data rate at a target symbol error rate (SER) and for a given power spectral density (PSD). Simulation results of the new scheme are presented for different measured PLC channels with impulsive noise and are compared with those of the classical discrete multitone modulation (DMT) approach. Then, it is shown that the proposed scheme offers higher throughput than DMT or less sensitiveness to impulse noise effects.

A simple generalized neuro-fuzzy operator for efficient removal of impulse noise from highly corrupted digital images

Abstract: A generalized neuro-fuzzy (NF) operator for removing impulse noise from highly corrupted digital images is presented. The fundamental building block of the operator is a simple 3-input 1-output NF filter. The operator is constructed by combining a desired number of NF filters with a postprocessor. Each NF filter in the structure evaluates a different pixel neighborhood relation. Hence, the number of NF filters in the structure can be varied to obtain the desired filtering performance. Internal parameters of the NF filters are adaptively optimized by training by using a simple artificial training image that can easily be generated in a computer. Simulation results indicate that the proposed operator outperforms popular conventional as well as state-of-the-art impulse noise removal operators and offers superior performance in removing impulse noise from highly corrupted images while efficiently preserving image details and texture.

A neighborhood evaluated adaptive vector filter for suppression of impulse noise in color images

Abstract: A new adaptive vector filter is proposed for impulse noise suppression and its relationship with the recent impulse reduction filters is investigated. The new filter detects outliers presented in the image through a novel neighborhood evaluation process, which significantly improves the accuracy of noise detection and detail preservation. The computational complexity of the new filter is very competitive. Its two parameters can be configured efficiently using online/offline optimization processes. Extensive simulations indicated that the new filter outperforms other prior-art methods in suppressing impulse noise in natural color images.

Various methods and apparatuses for imulse noise mitigation

Abstract: Methods and apparatuses for reducing effects of impulse noise in a DSL transmitter receiver device are described. According to certain embodiment, the method includes using a periodicity associated with the impulse noise affecting a DSL transmitter receiver device to determine data frames that are affected by the impulse noise, and sending a reduced data rate during those frames. In certain embodiments, no data is sent during those frames. The method further includes using a high margin bits and gain table, instead of a normal bits and gain table.

Robust adaptive MMSE/DFE multiuser detection in multipath fading channel with impulse noise

Abstract: The direct-sequence code-division multiple-access (DS/CDMA) technique is extensively used for cellular, personal, and mobile radio communication systems. However, the conventional channel estimators cannot provide accurate channel information for multiuser detection in the presence of impulsive noise and Doppler spread, especially in the time-varying fading channel. We propose a linear-trend tracking method for estimating the impulse response of the time-varying channel via a robust Kalman filtering with a scheme that can automatically adjust the variance of the driving noise. The proposed method need not identify the parameters of the channel model and is insensitive to the speed of channel variation. Following channel estimation, a robust multiuser detection algorithm is developed via a Kalman-based decision feedback equalization (DFE). A nonlinear limitation function is incorporated to mitigate the effects of channel estimation error and impulsive noise and to prevent severe error propagation. Simulation results conclude that the performance of the DS/CDMA system is improved by using the proposed receiver.

Image Denoising by Statistical Area Thresholding

Abstract: Area openings and closings are morphological filters which efficiently suppress impulse noise from an image, by removing small connected components of level sets. The problem of an objective choice of threshold for the area remains open. Here, a mathematical model for random images will be considered. Under this model, a Poisson approximation for the probability of appearance of any local pattern can be computed. In particular, the probability of observing a component with size larger than k in pure impulse noise has an explicit form. This permits the definition of a statistical test on the significance of connected components, thus providing an explicit formula for the area threshold of the denoising filter, as a function of the impulse noise probability parameter. Finally, using threshold decomposition, a denoising algorithm for grey level images is proposed.

Ofdm reception device

Abstract: An OFDM reception device detects a time at which impulse noise occurs in a received OFDM signal, and specifies a start position candidate period that does not have intersymbol interference and is estimated to have a guard interval signal in a symbol. When setting a FFT window of an effective symbol length in a symbol duration of each symbol, if the impulse noise occurrence time is included in the symbol, the OFDM reception device determines a start position of the FFT window within a range of the start position candidate period so as to exclude the impulse noise occurrence time as much as possible.

A new choice of penalty function for robust multiuser detection based on M-estimation

Abstract: In this letter, we propose a new robust MUD, called /spl alpha/ detector, for non-Gaussian noise. We consider the Gaussian-mixture model for non-Gaussian or impulsive noise. Our technique outperforms the decorrelator and the minimax detectors in highly impulsive noise. The proposed method uses a parametric cost function, where the parameter /spl alpha/ is selected using the difference between the asymptotic variance of estimation error of the /spl alpha/ detector and that of the minimax detector.

ABST M-Type K-Nearest Neighbor (ABSTM-KNN) for Image Denoising

Abstract: We present the Ansari-Bradley-Siegel-Tukey M-type K-nearest neighbor (ABSTM-KNN) filter to remove impulse noise from corrupted images. Extensive simulations have demonstrated that the proposed filter consistently outperforms other filters by balancing the tradeoff between noise suppression and detail preservation.

Digital signal disturbed by impulsive noise

Abstract: This paper presents and comments on test results and measurement procedures carried out mainly in the laboratory to investigate the degree of immunity of DTV reception in the presence of impulse noise. The objective of these tests was to compare the resilience to this type of noise provided by the DTV standards: ATSC, DVB-T and ISDB-T. The field test in the city of Sa/spl tilde/o Paulo, Brazil, showed a high and unforeseen rate of places presenting considerable degradation caused by impulsive noise. Previous studies do not reflect the reality of the impulse noise found in the Brazilian environment. Under these circumstances, a need arises for simulating interference conditions caused by ignition motors, hairdryers, blenders, etc, in the laboratory. Our laboratory tests utilized an impulse noise generator that was constructed especially to emulate ignition noise, but which was shown to be equally satisfactory in emulating other kinds of impulse noise. This paper also describes the operating principles and specifications of the impulse noise generator.