Removing Random-Valued Impulse Noises by a Two-Staged Nonlinear Filtering Method

Digital images are frequently contaminated by impulse noise(IN)during acquisition and transmission.The removal of this noise from images is essential for their further processing.In this paper,a two-staged nonlinear filtering algorithm is proposed for removing random-valued impulse noise(RVIN)from digital images.Noisy pixels are identified and corrected in two cascaded stages.The statistics of two subsets of nearest neighbors are employed as the criterion for detecting noisy pixels in the first stage,while directional differences are adopted as the detector criterion in the second stage.The respective adaptive median values are taken as the replacement values for noisy pixels in each stage.The performance of the proposed method was compared with that of several existing methods.The experimental results show that the performance of the suggested algorithm is superior to those of the compared methods in terms of noise removal,edge preservation,and processing time.

A detail-preserving random-valued impulse noise removal algorithm based on S-ROAD

In a random-valued impulse noise corrupted image, in order to remove impulse noise and, meanwhile, efficiently preserve image edges and details, a novel two-phase detail- preserving random-valued impulse noise removal algorithm is proposed. At the noise detecting phase, an image statistic called S-estimate based rank-ordered absolute difference （S- ROAD） is presented to distinguish image edge and detail pixels from impulse noise pixels in a noise corrupted image. By introducing S-estimate into ROAD statistic, the interference caused by the image edges and details in the ROAD statistic is eliminated. With the S-ROAD statistic, most of the noise pixels, including the noise at edges and details, can be distinguished. At the noise pixels filtering phase, a two-threshold iterative method is used to restore the identified noise pixels and the estimate precision is improved; thus, the image details can be efficiently preserved. Experimental results show that the proposed method provides a significant improvement over many existing filters in terms of both subjective and objective evaluations.

Direction finding of bistatic MIMO radar in strong impulse noise

For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in suppressing impulse noise and achieving superior direction finding performance using the maximum likelihood(ML)estimation method.A quantum equilibrium optimizer algorithm(QEOA)is devised to resolve the corresponding objective function for efficient and accurate direc-tion finding.The results of simulation reveal the capability of the presented method in success rate and root mean square error over existing direction-finding methods in different application situations,e.g.,locating coherent signal sources with very few snapshots in strong impulse noise.Other than that,the Cramér-Rao bound(CRB)under impulse noise environment has been drawn to test the capability of the presented method.

Localization for mixed near-field and far-field sources under impulsive noise

In order to solve the problem that the performance of traditional localization methods for mixed near-field sources(NFSs)and far-field sources(FFSs)degrades under impulsive noise,a robust and novel localization method is proposed.After eliminating the impacts of impulsive noise by the weighted out-lier filter,the direction of arrivals(DOAs)of FFSs can be estimated by multiple signal classification(MUSIC)spectral peaks search.Based on the DOAs information of FFSs,the separation of mixed sources can be performed.Finally,the estimation of localizing parameters of NFSs can avoid two-dimension spectral peaks search by decomposing steering vectors.The Cramer-Rao bounds(CRB)for the unbiased estimations of DOA and range under impulsive noise have been drawn.Simulation experiments verify that the proposed method has advantages in probability of successful estimation(PSE)and root mean square error(RMSE)compared with existing localization methods.It can be concluded that the proposed method is effective and reliable in the environment with low generalized signal to noise ratio(GSNR),few snapshots,and strong impulse.

Characteristics analysis of muzzle impulse noise based on wavelet energy spectrum

Because muzzle impulse noise could cause damage to or have an intluence on the operator, tiae ettecnve protecnve measures should be taken. Therefore, correct analysis of impulse noise characteristics is very significant. Considering the shortcomings of fast Fourier transform method （FFT） in analysis of muzzle impulse noise frequency characteristics, wavelet energy spectrum method is put forward. Based on specific experiment data, the frequency characteristics and spectral energy dis tribution can be obtained. The experiment results show that wavelet energy spectrum method is applicable in muzzle impulse noise characteristic analysis.

Impulsive Noise Cancellation in OFDM System Using Low Density Parity Check

An effective communication application necessitates the cancellation of Impulsive Noise(IN)from Orthogonal Frequency Division Multiplexing(OFDM),which is widely used for wireless applications due to its higher data rate and greater spectral efficiency.The OFDM system is typically corrupted by Impulsive Noise,which is an unwanted short-duration pulse with random amplitude and duration.Impulsive noise is created by humans and has non-Gaussian characteristics,causing problems in communication systems such as high capacity loss and poor error rate performance.Several techniques have been introduced in the literature to solve this type of problem,but they still have many issues that affect the performance of the presented methods.As a result,developing a new hybridization-based method is critical for accurate method performance.In this paper,we present a hybrid of a state space adaptive filter and an information coding technique for cancelling impulsive noise from OFDM.The proposed method is also compared to Least Mean Square(LMS),Normalized Least Mean Square(NLMS),and Recursive Least Square(RLS)adaptive filters.It has also been tested using the binary phase-shift keyed(BPSK),four quadrature amplitude modulation(QAM),sixteen QAM,and thirty-two QAM modulation techniques.Bit error Rate(BER)simulations are used to evaluate system performance,and improved performance is obtained.Furthermore,the proposed method is more effective than recent methods.

Image Filter for Removal of Impulse Noise Based on Directional Derivatives

One of the most common image processing tasks involves the removal of noise from images. Noise can be introduced during image capture, during transmission, or during storage. For design purposes, noise sources are frequently approximated by random variables with a known probability distribution. One common noise model corrupts a signal by introducing impulses. And the surface of the image disturbed by impulse noise displays many peaks or vales. According to the characteristic of impulse noise, a novel algorithm is proposed to the detection of impulse noise point from images based on directional derivatives. First, the theory of calculus on directional derivatives is introduced in detail. Then it is applied to the field of image to removing noise with the discrete form derived from its continuous mathematical model. And a number of contrasting simulations illustrate that our algorithm not only can preserve the structure information while removing impulse noise but also can mostly save the gray value of the pixels undisturbed by noise. In addition, the comparisons of the filtering performance for removing impulse noise are analyzed in detail in the case of different noise densities, and also show that the algorithm suggested outperforms the conventional filter algorithms such as mean filter, median filter and so on in speed and impulse noise reduction, especially in random-valued impulse noise reduction. So it is a very good alternative to the existing schemes.

Direction of arrival estimation method based on quantum electromagnetic field optimization in the impulse noise

In order to resolve direction finding problems in the impulse noise,a direction of arrival(DOA)estimation method is proposed.The proposed DOA estimation method can restrain the impulse noise by using infinite norm exponential kernel covariance matrix and obtain excellent performance via the maximumlikelihood(ML)algorithm.In order to obtain the global optimal solutions of this method,a quantum electromagnetic field optimization(QEFO)algorithm is designed.In view of the QEFO algorithm,the proposed method can resolve the difficulties of DOA estimation in the impulse noise.Comparing with some traditional DOA estimation methods,the proposed DOA estimation method shows high superiority and robustness for determining the DOA of independent and coherent sources,which has been verified via the Monte-Carlo experiments of different schemes,especially in the case of snapshot deficiency,low generalized signal to noise ratio(GSNR)and strong impulse noise.Beyond that,the Cramer-Rao bound(CRB)of angle estimation in the impulse noise and the proof of the convergence of the QEFO algorithm are provided in this paper.

Direction-Based Adaptive Switching Filter for Removing High-Density Impulse Noise

A direction-based adaptive switching(DBAS) filter is presented for the removal of high-density impulse noise in images. The extrema detection and 28-directional detection are employed to discriminate the pixels as noisy or noise-free. If a pixel is classified as noisy, it will be replaced by a median or a mean value within an adaptive filter window with respect to different noise densities. Simulation results show that the miss-detection ratio and false-alarm ratio are both very low even at noise level as high as 90%. At the same time, better results are obtained in terms of the qualitative and quantitative measures. The peak signal-to-noise ratios increase by nearly 1 dB compared with other existing algorithms. In addition, the computation time is around 10 s for test images with resolutions of 512×512since the proposed approach has low complexity.

Iterative Adaptive Median Filter for Impulse Noise Cancellation

Based on the characteristics of impulse noises, the authors establish a new filter, Iterative Adaptive Median Filter （IAMF）. Acccording to the characteristics of images polluted by impulse noises, they establish weight function combined with iterative algorithm to eliminate noises. In IAMF filter process, because the noise sixes do not participate in the computation, they do not influence the normal points in the image, therefore IAMF can retain the detail well, maintain the good clarity after processing image, and simultaneously reduce the computation. Experiments showed that IAMF have ideal denoising effect for the images polluted by the impulse noises; especially when the noise rates are more than 0.5, IAMF is mote prominent, even when the noise rotes are more than 0.9, IAMF can achieve a satisfactory results.

Accurate Tools for Analyzing the Behavior of Impulse Noise Reduction Filters in Color Images

Effective cancellation of noise and preservation of color/structural information are features of paramount importance for any filter devoted to impulse noise removal in color images. In this paper novel full-reference tools for analyzing the behavior of this family of filters are presented. The proposed approach is based on the classification of color errors into two main classes that separately take into account the inaccuracy in removing noise pulses and the filtering distortion. The distortion errors are then classified into two subclasses for a deeper analysis of the filtering behavior. Computer simulations show that the proposed method gives more accurate results than using other measures of filtering performance in the literature. Furthermore, the method can easily yield the spatial location of the different filtering features in the image.

Research of multi-channel impulse noise detection algorithms based on template

Attenuating the undesired audio noise generated by impulse noise,such as shot and scream of brakes,is specially useful for real-time audio recording of TV or broadcasting live report.On the basis of impulse noise detection algorithms based on template,this paper improves the method of establishing the template by using multiple microphones to pick up noise corrupted signals and impulse noises in the environment.The universal of thresholds is found and a detection algorithm with slope as the characteristic is proposed by comparing a variety of feature extraction algorithms.The proposed algorithm gets a significant improvement in testing speed and accuracy,which means it is suitable for real-time processing of audio signals.

Effect of Impulse Noise on Wireless Relay Channel

Relay Network is most suited wireless communication technique for future Smart Grid, because it has a lot of advantages such as reliability against failures and offers redundancy, self-configuring and self-healing. For example if one nod or path is blocked, it can find a neighbour node, by different algorithms schemes. The purpose of this paper is to simulate wireless relay channel model in presence of impulse noise and computing the BER performance of channel data. It makes to be useful for a designer to predicting error and behaviour of a channel for optimum design, to be able choose a robust channel.

Adaptive Threshold Median Filter for Multiple-Impulse Noise

Attenuating the noises plays an essential role in the image processing. Almost all the traditional median filters concern the removal of impulse noise having a single layer, whose noise gray level value is constant. In this paper, a new adaptive median filter is proposed to handle those images corrupted not only by single layer noise. The adaptive threshold median filter （ATMF） has been developed by combining the adaptive median filter （AMF） and two dynamic thresholds. Because of the dynamic threshold being used, the ATMF is able to balance the removal of the multiple-impulse noise and the quality of image. Comparison of the proposed method with traditional median filters is provided. Some visual examples are given to demonstrate the performance of the proposed filter.

Efficient Global Threshold Vector Outlyingness Ratio Filter for the Removal of Random Valued Impulse Noise

This research paper proposes a filter to remove Random Valued Impulse Noise (RVIN) based on Global Threshold Vector Outlyingness Ratio (GTVOR) that is applicable for real time image processing. This filter works with the algorithm that breaks the images into various decomposition levels using Discrete Wavelet Transform (DWT) and searches for the noisy pixels using the outlyingness of the pixel. This algorithm has the capability of differentiating high frequency pixels and the “noisy pixel” using the threshold as well as window adjustments. The damage and the loss of information are prevented by means of interior mining. This global threshold based algorithm uses different thresholds for different quadrants of DWT and thus helps in recovery of noisy image even if it is 90% affected. Experimental results exhibit that this method outperforms other existing methods for accurate noise detection and removal, at the same time chain of connectivity is not lost.

DOA Estimation Based on Sparse Representation of the Fractional Lower Order Statistics in Impulsive Noise

This paper is mainly to deal with the problem of direction of arrival(DOA) estimations of multiple narrow-band sources impinging on a uniform linear array under impulsive noise environments. By modeling the impulsive noise as α-stable distribution, new methods which combine the sparse signal representation technique and fractional lower order statistics theory are proposed. In the new algorithms, the fractional lower order statistics vectors of the array output signal are sparsely represented on an overcomplete basis and the DOAs can be effectively estimated by searching the sparsest coefficients. To enhance the robustness performance of the proposed algorithms,the improved algorithms are advanced by eliminating the fractional lower order statistics of the noise from the fractional lower order statistics vector of the array output through a linear transformation. Simulation results have shown the effectiveness of the proposed methods for a wide range of highly impulsive environments.

Performance analysis of Turbo-Codes in communication channels with impulsive noise

Performance of Turbo-Codes in communication channels with impulsive noise is analyzed. First, mathematical model of impulsive noise is presented because it has non-Gaussian nature and is found in many wireless channels due to impulsive phenomena of radio-frequency interference. Then, with linear Log-MAP decoding algorithm for its low complexity, Turbo-Codes are adopted and analyzed in such communication channels. To confirm the performance of the proposed method, simulations on both static and fully interleaved flat Rayleigh fading channels with impulsive noise have been carried out. It is shown that Turbo-Codes have a better performance than the conventional methods （e.g. convolutionally coded system）.

Receiver design of UWB radio systems for an impulsive noise environment

The performance of UWB (ultrawide bandwidth) radio systems under an impulsive noise environment is first investigated. In the analysis, the Middleton's class A model is used as a model of the impulsive noise. At first, the statistical characteristics of the inphase and quadrature components of the impulsive noise are investigated, and it is proved that unlike Gaussian noise, these components are dependent especially on the impulsive noise with small impulsive indices. The probability that the high amplitude noise is emitted in the inphase component which becomes firstly larger and then smaller for the larger quadrature component of impulsive noise is presented. Next, the performance of conventional UWB radio systems designed for the Gaussian noise under the impulsive noise is evaluated and numerical results show that the performance of the conventional UWB radio systems is much degraded by the effect of the impulsive noise. Using the dependence between the inphase and quadrature components of the impulsive noise, a novel UWB receiver designed for impulsive noise is proposed and the performance improvement achieved by the receiver is evaluated. Numerical results show that the performance of UWB radio systems is much improved by employing the proposed receiver.

Precoder Design and Impulsive Noise Mitigation Scheme for Industrial Wireless Communications

In industrial wireless scenarios,the impulsive noise(IN)incurred by machine running or operation causes a serious influence on the powerlimited industrial wireless communications.It is challenging to ensure efficient and reliable transmission with quality of service(QoS)guarantee for machinetype communication devices(MTCDs).Considering the IN in the industrial process,this paper establishes the multiuser multiple-input single-output(MU-MISO)orthogonal frequency division multiplexing(OFDM)system model,which combines transmitter and receiver design.Two precoding schemes are designed to improve communication effectiveness at the transmitter.More specifically,the precoder design scheme which combines semi-definite relaxation(SDR)with difference-of-two-convex-function(D.C.)iterative algorithm,is developed by utilizing the Dinkelbach method to improve the system effectiveness.To decrease the computational complexity,we devise the quadratic-based fractional programming(QFP)algorithm,which decouples the variables by using a quadratic transform method.On this basis,the IN mitigation scheme is studied to reduce the system error rate(SER)at the receiver.With the goal of improving the reliability of industrial wireless communications,we propose a hybrid nonlinear IN mitigation(HNINM)scheme and then derive its closed-form expression of SER.The simulation results show that the proposed QFP algorithm achieves superior performance while the HNINM scheme decreases the SER of industrial wireless communications.