Showing papers on "Impulse noise published in 2008"

Simple adaptive median filter for the removal of impulse noise from highly corrupted images

Abstract: This paper presents a simple, yet efficient way to remove impulse noise from digital images. This novel method comprises two stages. The first stage is to detect the impulse noise in the image. In this stage, based on only the intensity values, the pixels are roughly divided into two classes, which are "noise-free pixel" and "noise pixel". Then, the second stage is to eliminate the impulse noise from the image. In this stage, only the "noise-pixels" are processed. The "noise-free pixels " are copied directly to the output image. The method adaptively changes the size of the median filter based on the number of the "noise-free pixels " in the neighborhood. For the filtering, only "noise-free pixels " are considered for the finding of the median value. The results from 100 test images showed that this proposed method surpasses some of the state-ofart methods, and can remove the noise from highly corrupted images, up to noise percentage of 95%. Average processing time needed to completely process images of 1600times1200 pixels with 95% noise percentage is less than 2.7 seconds. Because of its simplicity, this proposed method is suitable to be implemented in consumer electronics products such as digital television, or digital camera.

Two-phase approach for deblurring images corrupted by impulse plus gaussian noise

Abstract: The restoration of blurred images corrupted with impulse noise is a difficult problem which has been considered in a series of recent papers. These papers tackle the problem by using variational methods involving an L1-shaped data-fidelity term. Because of this term, the relevant methods exhibit systematic errors at the corrupted pixel locations and require a cumbersome optimization stage. In this work we propose and justify a much simpler alternative approach which overcomes the above-mentioned systematic errors and leads to much better results. Following a theoretical derivation based on a simple model, we decouple the problem into two phases. First, we identify the outlier candidates---the pixels that are likely to be corrupted by the impulse noise, and we remove them from our data set. In a second phase, the image is deblurred and denoised simultaneously using essentially the outlier-free data. The resultant optimization stage is much simpler in comparison with the current full variational methods and the outlier contamination is more accurately corrected. The experiments show that we obtain a 2 to 6 dB improvement in PSNR. We emphasize that our method can be adapted to deblur images corrupted with mixed impulse plus Gaussian noise, and hence it can address a much wider class of practical problems.

An Efficient Edge-Preserving Algorithm for Removal of Salt-and-Pepper Noise

Abstract: In this letter, a novel algorithm for removing salt-and-pepper noise from corrupted images is presented. We employ an efficient impulse noise detector to detect the noisy pixels, and an edge-preserving filter to reconstruct the intensity values of noisy pixels. Extensive experimental results demonstrate that our method can obtain better performances in terms of both subjective and objective evaluations than those state-of-the-art impulse denoising techniques. Especially, the proposed method can preserve edges very well while removing impulse noise. Since our algorithm is algorithmically simple, it is very suitable to be applied to many real-time applications.

Impulse noise cancellation in OFDM: an application of compressed sensing

Abstract: We use recently developed convex programming techniques to reconstruct arbitrary sparse signals observed through projections onto a small-dimensional space in background noise in order to estimate and remove impulsive noise in an OFDM system. We develop deterministic construction of projection matrices that provably guarantee reconstruction with high probability. Finally, we compare the achievable rate using our novel method with some simple capacity lower and upper bounds and with the recently obtained capacity of the Gaussian erasure channel. For practical impulse probability the proposed scheme appears to be competitive. This scheme may find some application in DSL and powerline communications, where transmission is typically affected by intersymbol interference, Gaussian noise and impulsive noise.

Universal Impulse Noise Filter Based on Genetic Programming

Abstract: In this paper, we present a novel method for impulse noise filter construction, based on the switching scheme with two cascaded detectors and two corresponding estimators. Genetic programming as a supervised learning algorithm is employed for building two detectors with complementary characteristics. The first detector identifies the majority of noisy pixels. The second detector searches for the remaining noise missed by the first detector, usually hidden in image details or with amplitudes close to its local neighborhood. Both detectors are based on the robust estimators of location and scale-median and MAD. The filter made by the proposed method is capable of effectively suppressing all kinds of impulse noise, in contrast to many existing filters which are specialized only for a particular noise model. In addition, we propose the usage of a new impulse noise model-the mixed impulse noise, which is more realistic and harder to treat than existing impulse noise models. The proposed model is the combination of commonly used noise models: salt-and-pepper and uniform impulse noise models. Simulation results show that the proposed two-stage GP filter produces excellent results and outperforms existing state-of-the-art filters.

An Efficient Procedure for Removing Random-Valued Impulse Noise in Images

Abstract: In this letter, we present an efficient algorithm for the removal of random-valued impulse noise from a corrupted image by using a reference image The proposed method uses a statistic of rank-ordered relative differences to identify pixels which are likely to be corrupted by impulse noise Once a noisy pixel is identified, its value is restored by a simple weighted mean filter Simulation results indicate that our algorithm provides a significant improvement over many other existing techniques

Impulsive Noise Characterization of In-Vehicle Power Line

Abstract: Impulsive noise can have a great influence on the performance of in-vehicle power line communication systems. Intensive noise measurements in the time domain were thus carried out on five different vehicles. Preliminary trials were first made on a stationary vehicle and the motor idling, but the characteristics of the measured low-amplitude pulses greatly vary from one car to another. We thus emphasize the characteristics of high-amplitude pulses, greater than 70 mV, observed when the vehicles were moving in traffic, during a 20-min trip. Noise is statistically characterized in terms of duration, frequency content, peak amplitude, and time interval between successive pulses. Stochastic models based on mathematical distribution functions and fitting the experimental distribution of the various pulse characteristics are proposed. It has been found that interarrival time, i.e., the time interval between two successive pulses, is rather short and would be thus the most critical parameter when optimizing the power line communication physical layer.

An Improved Decision-Based Algorithm for Impulse Noise Removal

Abstract: The paper proposes an improved fast and efficient decision-based algorithm for the restoration of images that are highly corrupted by Salt-and-Pepper noise. The new algorithm utilizes previously processed neighboring pixel values to get better image quality than the one utilizing only the just previously processed pixel value. The proposed algorithm is faster and also produces better result than a Standard Median Filter (SMF), Adaptive Median Filters (AMF), Cascade and Recursive non-linear filters. The proposed method removes only the noisy pixel either by the median value or by the mean of the previously processed neighboring pixel values. Different images have been tested by using the proposed algorithm (PA) and found to produce better PSNR and SSIM values.

Impulse Noise Removal From Digital Images by a Detail-Preserving Filter Based on Type-2 Fuzzy Logic

Abstract: A novel image filter based on type-2 fuzzy logic techniques is proposed for detail-preserving restoration of digital images corrupted by impulse noise. The performance of the proposed filter is evaluated for different test images corrupted at various noise densities and also compared with representative conventional as well as state-of-the-art impulse noise filters from the literature. Experimental results show that the proposed filter exhibits superior performance over the competing operators and is capable of efficiently suppressing the noise in the image while at the same time effectively preserving thin lines, edges, texture, and other useful information within the image.

A Novel Two-Stage Impulse Noise Removal Technique Based on Neural Networks and Fuzzy Decision

Abstract: In this paper, a novel two-stage noise removal algorithm to deal with impulse noise is proposed. In the first stage, an adaptive two-level feedforward neural network (NN) with a backpropagation training algorithm was applied to remove the noise cleanly and keep the uncorrupted information well. In the second stage, the fuzzy decision rules inspired by the human visual system (HVS) are proposed to classify the image pixels into human perception sensitive class and nonsensitive class, and to compensate the blur of the edge and the destruction caused by the median filter. An NN is proposed to enhance the sensitive regions with higher visual quality. According to the experimental results, the proposed method is superior to conventional methods in perceptual image quality as well as the clarity and smoothness in edge regions.

Mitigating near-field interference in laptop embedded wireless transceivers

Abstract: In laptop and desktop computers, clocks and busses generate significant radio frequency interference (RFI) for the embedded wireless data transceivers. RFI is impulsive in nature. When detecting a signal in additive impulsive noise, Spaulding and Middleton showed a potential improvement in detection of 25 dB at a bit error rate of 10-5 when using a Bayesian detector instead of a standard correlation receiver. In this paper, we model impulsive noise using Middleton class A and symmetric alpha stable (SaS) models. The contributions of this paper are to evaluate (1) the performance vs. complexity of parameter estimation algorithms, (2) the closeness of fit of parameter estimation algorithms to measured RFI data from the computer platform, (3) the communication performance vs. computational complexity tradeoffs for the correlation receiver, Wiener filter, and Bayesian detector, and (4) the performance of myriad filtering in combating RFI interference modeled as SaS interference.

On reliable communications over channels impaired by bursty impulse noise

Abstract: We consider digital communications over channels affected by impulse noise. A two-state Markov channel model is adopted, which, unlike the memoryless models generally adopted in the literature, allows to describe the typical bursty nature of the impulse noise. We derive an algorithm for optimal maximum-a-posteriori symbol detection, which is first exploited for evaluating, by means of information-theoretical arguments, the ultimate performance limits imposed by the channel, and then is proposed as detection algorithm for practical communication systems employing iterative detection/decoding. The proposed scheme is finally shown to perform significantly better than the conventional ones which neglect the channel memory, and fairly close to the achievable theoretical limits.

On characterizing multiple access interference in TH-UWB systems with impulsive noise models

Abstract: The Gaussian mixture distribution, the Middleton class A noise model and the Laplace distribution are used for approximately characterizing the statistics of the multiple access interference in time-hopping ultra-wideband communication systems. The similarities and differences of these approximations are discussed and the validities of these models are assessed in terms of the probability density function of the interference and the bit error rate performance.

Joint Time-domain/Frequency-domain Impulsive Noise Reduction in OFDM-based Power Line Communications

Abstract: Impulsive noise is one of the major challenges in power line communications and can cause serious problems in OFDM-based PLC systems. In this paper, we propose a combined Time-Domain/Frequency-domain technique for impulsive noise reduction in OFDM-based PLC systems. The performance of the proposed technique is studied against well known time-domain nonlinearities by means of computer simulations. The obtained simulation results show that the Combined TD/FD technique performs better than practically used nonlinearities and can reduce the adverse effect of impulsive noise significantly.

High performance detection filter for impulse noise removal in images

Abstract: A high performance detection (HPD) filter is proposed for impulse noise removal in images. In this approach, the noisy pixels are detected iteratively through several phases, based on a set of unique similarity criteria. Simulation results show that the HPD filter outperforms others at medium to high noise rates and suppresses impulse noise effectively while preserving image details, even thin lines.

Impulse noise removal in speech using wavelets

Abstract: A new method for removing impulse noise from speech in the wavelet transform domain is proposed. The method utilizes the multi-resolution property of the wavelet transform, which provides finer time resolution at the higher frequencies than the short-time Fourier transform (STFT), to effectively identify and remove impulse noise. It uses two features of speech to discriminate speech from impulse noise: one is the slow time-varying nature of speech and the other is the Lipschitz regularity of the speech components. On the basis of these features, an algorithm has been developed to identify and suppress wavelet coefficients that correspond to impulse noise. Experiment results show that the new method is able to significantly reduce impulse noise without degrading the quality of the speech signal or introducing any audible artifacts.

On Error Saturation Nonlinearities for LMS Adaptation in Impulsive Noise

Abstract: This correspondence extends the analytic results in [N. J. Bershad, ldquoOn error nonlinearities in LMS adaptation,rdquo IEEE Transactions on Acoustics, Speech and Signal Processing, vol. ASSP-36, no. 4, pp. 440-452, April 1988] to least mean-square (LMS) adaptation in impulsive observation noise. A scalar recursion for the weight misadjustment is derived for the white input data case. Monte Carlo simulations verify the accuracy of the theoretical model. The theoretical recursion is then used to study the effects of the impulse noise on algorithm convergence speed and steady-state weight misadjustment for a wide variety of parameter values.

An Improved Switching Median filter for Uniformly Distributed Impulse Noise Removal

Abstract: The performance of an image filtering system depends on its ability to detect the presence of noisy pixels in the image. Most of the impulse detection schemes assume the presence of salt and pepper noise in the images and do not work satisfactorily in case of uniformly distributed impulse noise. In this paper, a new algorithm is presented to improve the performance of switching median filter in detection of uniformly distributed impulse noise. The performance of the proposed scheme is demonstrated by the results obtained from computer simulations on various images. Keywords—Switching median filter, Impulse noise, Image filtering, Impulse detection.

Optimization of Turbo Decoding Performance in the Presence of Impulsive Noise Using Soft Limitation at the Receiver Side

Abstract: The impulsive noise is one of the main reasons for bit or burst errors in power line transmission. The use of a level limiter is a simple and intuitive technique to mitigate the noxious effect of impulsive noise in such channels. However the appropriate threshold determination remains empirical. In this paper, a suitable calculation of the log-likelihood ratio (LLR) for Turbo codes (TC) in an impulsive environment is performed both for BPSK and OFDM systems. As main results of the present work, we first determine the LLR channel value when using a limiter. Furthermore, based on a receiver operating characteristic (ROC) analysis, we derive the optimal detection threshold of the limiter. Finally, the results are validated by simulation with HomePlug AV physical layer specification.

Adaptive Fuzzy Median Filter for Images Corrupted by Impulse Noise

Abstract: Median filter was once the most popular nonlinear filter for removing impulse noise because of its good denoising power. In this paper, we present a novel adaptive fuzzy median filter to the restoration of salt & pepper impulse noise-corrupted image, which is particularly effective at removing highly impulsive noise. First we estimate noise level based on fussy set theory, then process the corrupted pixel or extend the size of filtering window, at last get the appropriate median value to replace the noisy pixel. The proposed filter has the benefits that it is simple and it assumes no a priori knowledge of specific input image. To demonstrate the capability of our filtering approach, it was tested on several different image enhancement problems. Experimental results have shown that the proposed algorithm works very well not only for images with lower percentage of impulse noises but also with higher percentage of impulse noise.

A New Kind of Weighted Median Filtering Algorithm Used for Image Processing

Abstract: Aimed at the excellence and shortcoming of the traditional median filtering algorithm, this paper proposes a new adaptive weighted median filtering algorithm. The new algorithm first determines noise points in image through noise detection, then adjusts the size of filtering window adaptively according to number of noise points in window, the pixel points in the filtering window are grouped adaptively by certain rules and gives corresponding weight to each group of pixel points according to similarity, finally the noise detected are filtering-treated by means of weighted median filtering algorithm. The result of computer simulation experiment indicates that the new algorithm can not only filter off noise effectively, but also favorably reserve image details with a filtering performance better than traditional median filtering algorithm.

Total variation regularisation of images corrupted by non-Gaussian noise using a quasi-Newton method

Abstract: The aim is to obtain efficient algorithms for image regularisation optimised for removing different types of noise. One can accomplish this by combining total variation regularisation with a noise-specific way to measure the fidelity between the noisy and the denoised images. To obtain a minimum of the resulting functional, a quasi-Newton method is proposed, which converges faster than the commonly used method of gradient descent. A unified algorithmic and theoretical framework for a general class of data-fidelity terms is presented. As examples, we consider Poisson noise and impulse noise.

Systems and methods for monitoring impulse noise

Abstract: Systems and methods for monitoring impulse noise are described. At least one embodiment is a method, which comprises detecting whether impulse noise is present and in response to detecting the presence of impulse noise, performing time domain analysis to determine whether one or more impulse noise sources are present based on minimum interarrival time and maximum impulse length. The method further includes performing frequency domain analysis to estimate frequencies associated with the one or more impulse noise sources and based on the time domain analysis and frequency domain analysis, providing a total number of impulse noise sources and frequencies associated with the impulse noise sources. In this regard, the embodiments described herein provide dual-speed monitoring of impulse noise in the form of short-term and long-term monitoring. The use of dual-speed monitoring ensures that dynamic changes in the impulse noise environment are quickly addressed and also ensures better characterization of multiple impulse noise sources in order to provide better impulse noise protection.

Soft-Decision Metrics for Coded Orthogonal Signaling in Symmetric Alpha-Stable Noise

Abstract: This paper derives new soft-decision metrics for coded orthogonal signaling in impulsive noise, more specifically symmetric alpha-stable noise. For the case of a known channel amplitude and known noise dispersion, exact metrics are derived both for Cauchy and Gaussian noise. For the case that the channel amplitude or the dispersion is unknown, approximate metrics are obtained in closed-form based on a generalized-likelihood ratio approach. The performance of the new metrics is compared numerically for a turbo-coded system, and the sensitivity to side information of the optimum receiver for Cauchy noise is considered. The gain that can be achieved by using a properly chosen decoding metric is quantified, and it is shown that this gain is significant. The application of the results to frequency hopping ad hoc networks is also discussed.

An Improved Median Filter Based on Efficient Noise Detection for High Quality Image Restoration

Abstract: To restore images corrupted by impulse noise, various image filtering strategies have been proposed. However, a common drawback of these methods is that the details and edges can not recovered satisfactorily when the noise level is high. A novel method based on efficient noise detection algorithm is proposed in this paper for effectively denoising extremely corrupted images and better details and edges preservation. The proposed method replaces only noisy pixel by either the median value or by a noise-free pixel value inside the selected filtering window. While uncorrupted pixels are remain unchanged. The key feature of the proposed method is very high noise detection accuracy, yielding zero miss-detection rate. Comparative studies of the proposed method and other methods for different images are made and the advantages of the proposed method are fully demonstrated.

Measurements of impulsive noise in broad-band wireless communication channels

Abstract: Electrical and mechanical equipments can be major sources of interference for wireless systems. This paper presents the effects of both noise and interference in a wide frequency band between 100 kHz and 3 GHz. Electromagnetic field (EMF) strength measurements of the impulsive noise taken at various locations such as computer labs, TV stations and hospitals are presented. Measurement results are fitted into a mathematical model and it is shown that the amplitude probability distribution (APD) functions derived from the measurements can be described by the Middleton Class-A model.

A robust neuro-fuzzy network approach to impulse noise filtering for color images

Abstract: Based on an integration of a simple impulse detector and a robust neuro-fuzzy (RNF) network, an effective impulse noise filter for color images is presented. It consists of two modes of operation, namely, training and testing (filtering). During training, the impulse detector is used to locate the noisy pixels in the color images for optimizing the RNF network. During testing, if a pixel is detected as a corrupted one according to the impulse detector, the trained RNF network will be triggered to output a new pixel to replace it. The proposed impulse noise filter is distinguished by two properties. The first is the use of a simple impulse detector, which is efficient and yet effective in detecting the noisy pixels in color images. The other is the use of a novel membership function in the design of the adaptive RNF network, making the network robust to impulse noise. As demonstrated by the experimental results, the proposed filter not only has the abilities of noise attenuation and details preservation but also possesses desirable robustness and adaptive capabilities. It outperforms other conventional multichannel filters.

A Portable Wideband Impulsive Noise Location System

Abstract: Many power-system-related effects and sources of man-made noise cause impulsive interference. Due to its wideband nature, this type of interference is difficult to remove by filtering. This paper presents a system that is capable of locating and characterizing sources of impulsive interference. It is based on three separate asynchronous receiving units. The operating principle of the location system is outlined, and a prototype practical implementation is described. The location accuracies achieved both in the laboratory and in practical field trials are reported.