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.

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.

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.

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.

A preliminary study of the mechanism of compound hearing loss caused by ototoxic drugs combined with impulse noise

Background:Hearing loss(HL)is becoming increasingly common and is more commonly caused by noise,ototoxic substances,or a combination of ototoxic factors.However,so far,few studies have examined the mechanism by which compound factors cause HL.The only relevant study is about occupational ototoxic substances combined with environmental noise at 85-110 dB SPL.In this study,to address the shortcomings of existing research,we innovatively focused on HL induced by loud noise(impulse noise,>160 dB SPL)combined with common ototoxic drugs.The aim of this study was to establish and validate a mature animal model,and then to compare the characteristics of audiology,pathomorphology and molecular features,and to preliminarily predict pathogenesis in compound HL.Materials and Methods:We selected guinea pigs to construct in vivo HL model groups for different extents of exposure,including a blank control group,a single-drug group,a single-impulse noise group,and a compound group.The animal model of the mature compound HL group was established using gentamicin combined with impulse noise.We then performed audio-logical and pathological verification.We analyzed the auditory brainstem response(ABR),pathological morphology of the cochlea,and molecules(including important self-radicals,cytokines,and apoptosis signal trans-duction pathway proteins in the pathogenesis of drug-and noise-induced HL),compared the effect of different extents of exposure on HL,and preliminarily predict the pathogenic mechanism of compound HL.Results:Four groups of animal models were established successfully and verified by audiology and pathology.Regarding audiology,there were no sig-nificant differences in the ABR thresholds before exposure(p>0.05),but differences emerged among the groups after exposure.Notably,after 3,7,and 14 days of exposure,there were significant differences in the ABR thresholds between the compound group and both the drug and noise groups(p<0.01),and after 14 days,the HL of the compound group was much more severe(greater than the linear sum of single-factor HL group).Regarding the patho-morphology,compared with the control group,the cochleae were damaged to different degrees in the factor exposure groups.The drug group had the least severe HL,the noise group had serious HL(p<0.05),and the compound group had the most severe HL(p<0.01).The compound group's damage was greater than the linear sum of the single-factor group in many ways,such as the loss and damage of hair cells and cilia,disturbed morphology and arrangement of hair cells,protein metabolism,cell function,and structural defects on the epidermal plate(p<0.01).From a molecular perspective,the trend was similar to pathology and audiology,and the synergistic effect of ototoxic drugs and impulse noise significantly increased cytokine levels(IL-6,ICAM-1,8-OHDG,IL-1,and TNF-α),free radicals Malondialdehyde([MDA],▪OH,LPO,O•2ˉ),and the apoptosis signal transduction pathway protein.There were significant differences between the compound group and single-factor groups(p<0.05).Conclusion:Gentamicin,impulse noise,and compound factors were used to induce HL in animal models,which were verified by audiology and pathology,laying a foundation for future studies.After constructing the animal models,we found that 50 mg/kg of gentamicin for 10 days was a subinjury dose,and 50�impulse noise caused partial HL,but the two factors combined had a significant synergistic ototoxicity effect,which increased the level of oxidative stress and the waterfall response of inflammatory cytokines in the cochleae and enhanced the expression of apoptosis-related proteins,resulting in syn-ergistic pathomorphological and audiological injury.We preliminarily analyzed the pathogenic mechanism of compound HL,establishing the basis for further study of the mechanism,prevention,and treatment of this increasing global problem.

IMPULSE NOISE REMOVAL BY L1 WEIGHTED NUCLEAR NORM MINIMIZATION

In recent years,the nuclear norm minimization(NNM)as a convex relaxation of the rank minimization has attracted great research interest.By assigning different weights to singular values,the weighted nuclear norm minimization(WNNM)has been utilized in many applications.However,most of the work on WNNM is combined with the l 2-data-fidelity term,which is under additive Gaussian noise assumption.In this paper,we introduce the L1-WNNM model,which incorporates the l 1-data-fidelity term and the regularization from WNNM.We apply the alternating direction method of multipliers(ADMM)to solve the non-convex minimization problem in this model.We exploit the low rank prior on the patch matrices extracted based on the image non-local self-similarity and apply the L1-WNNM model on patch matrices to restore the image corrupted by impulse noise.Numerical results show that our method can effectively remove impulse noise.

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.

EFFICIENT BOX-CONSTRAINED TV-TYPE-l^1 ALGORITHMS FOR RESTORING IMAGES WITH IMPULSE NOISE

In this paper, we study the restoration of images simultaneously corrupted by blur and impulse noise via variational approach with a box constraint on the pixel values of an image. In the literature, the TV-l^1 variational model which contains a total variation （TV） regularization term and an l^1 data-fidelity term, has been proposed and developed. Several numerical methods have been studied and experimental results have shown that these methods lead to very promising results. However, these numerical methods are designed based on approximation or penalty approaches, and do not consider the box constraint. The addition of the box constraint makes the problem more difficult to handle. The main contribution of this paper is to develop numerical algorithms based on the derivation of exact total variation and the use of proximal operators. Both one-phase and two-phase methods are considered, and both TV and nonlocal TV versions are designed. The box constraint [0, 1] on the pixel values of an image can be efficiently handled by the proposed algorithms. The numerical experiments demonstrate that the proposed methods are efficient in computational time and effective in restoring images with impulse noise.

Carrier frequency offset and impulse noise estimation for underwater acoustic orthogonal frequency division multiplexing

The carrier frequency offset（CFO）and impulse noise always affect the performance of underwater acoustic communication_systems.The CFO and impulse noise could be estimated by using the null subcarriers to cancel the effects of the two types of interference.The null subcarriers estimation methods include optimal separate estimation and joint estimation.The separate estimation firstly estimates the CFO value and then estimates the impulse noise value.However,the CFO and impulse noise always affect each other when either of them is estimated separately.The performance could be improved by using the joint estimation.The results of simulations and experiments have showed that these two optimization methods have good performance and the joint estimation has better performance than the separate estimation method.There is 3 dB performance gain at the BER value of 10^（-2）when using the joint estimation method.Thus these methods could improve the system robustness by using the CFO compensation and impulse noise suppression.

Total Variation Based Parameter-Free Model for Impulse Noise Removal

We propose a new two-phase method for reconstruction of blurred im-ages corrupted by impulse noise.In the first phase,we use a noise detector to iden-tify the pixels that are contaminated by noise,and then,in the second phase,we reconstruct the noisy pixels by solving an equality constrained total variation mini-mization problem that preserves the exact values of the noise-free pixels.For images that are only corrupted by impulse noise(i.e.,not blurred)we apply the semismooth Newton’s method to a reduced problem,and if the images are also blurred,we solve the equality constrained reconstruction problem using a first-order primal-dual algo-rithm.The proposed model improves the computational efficiency(in the denoising case)and has the advantage of being regularization parameter-free.Our numerical results suggest that the method is competitive in terms of its restoration capabilities with respect to the other two-phase methods.

Distribution-Transformed Network for Impulse Noise Removal

This work aims to explore the restoration of images corrupted by impulse noise via distribution-transformed network (DTN), which utilizes convolutional neural network to learn pixel-distribution features from noisy images. Compared with the traditional median-based algorithms, it avoids the complicated pre-processing procedure and directly tackles the original image. Additionally, different from the traditional methods utilizing the spatial neighbor information around the pixels or patches and optimizing in an iterative manner, this work turns to capture the pixel-level distribution information by means of wide and transformed network learning. DTN fits the distribution at pixel-level with larger receptions and more channels. Furthermore, DTN utilities a residual block without batch normalization layer to generate a good estimate. In terms of edge preservation and noise suppression, the proposed DTN consistently achieves significantly superior performance than current state-of-the-art methods, particularly at extreme noise densities.

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.

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.

Minimum geometric power distortionless response beamforming against heavy-tailed noise of unknown statistics

A minimum geometric power distortionless response beamforming approach against impulsive noise （including all α- stable noise） of unknown statistics is proposed. Due to that definite logarithmic moments require no priori knowledge of impulsive noise, this new beamformer substitutes the logarithmic moments for the second-order moments and iteratively minimizes the ＂ge- ometric power＂ of the beamformer.s output snapshots, subjected to a linear constraint. Therefore, the proposed beamformer can provide significantly higher output geometric signal-to-noise-andinterference ratio. Moreover, the optimum weight vector is obtained by using a new iteration process. The simulation results prove that the new method is effective.

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.

A New Hybrid Model for Segmentation of the Skin Lesion Based on Residual Attention U-Net

Skin segmentation participates significantly in various biomedical applications,such as skin cancer identification and skin lesion detection.This paper presents a novel framework for segmenting the skin.The framework contains two main stages:The first stage is for removing different types of noises from the dermoscopic images,such as hair,speckle,and impulse noise,and the second stage is for segmentation of the dermoscopic images using an attention residual U-shaped Network(U-Net).The framework uses variational Autoencoders(VAEs)for removing the hair noises,the Generative Adversarial Denoising Network(DGAN-Net),the Denoising U-shaped U-Net(D-U-NET),and Batch Renormalization U-Net(Br-U-NET)for remov-ing the speckle noise,and the Laplacian Vector Median Filter(MLVMF)for removing the impulse noise.In the second main stage,the residual attention u-net was used for segmentation.The framework achieves(35.11,31.26,27.01,and 26.16),(36.34,33.23,31.32,and 28.65),and(36.33,32.21,28.54,and 27.11)for removing hair,speckle,and impulse noise,respectively,based on Peak Signal Noise Ratio(PSNR)at the level of(0.1,0.25,0.5,and 0.75)of noise.The framework also achieves an accuracy of nearly 94.26 in the dice score in the process of segmentation before removing noise and 95.22 after removing different types of noise.The experiments have shown the efficiency of the used model in removing noise according to the structural similarity index measure(SSIM)and PSNR and in the segmentation process as well.

An Optimized Implementation of a Novel Nonlinear Filter for Color Image Restoration

Image processing is becoming more popular because images are being used increasingly in medical diagnosis,biometric monitoring,and character recognition.But these images are frequently contaminated with noise,which can corrupt subsequent image processing stages.Therefore,in this paper,we propose a novel nonlinear filter for removing“salt and pepper”impulsive noise from a complex color image.The new filter is called the Modified Vector Directional Filter(MVDF).The suggested method is based on the traditional Vector Directional Filter(VDF).However,before the candidate pixel is processed by the VDF,theMVDF employs a threshold and the neighboring pixels of the candidate pixel in a 3×3 filter window to determine whether it is noise-corrupted or noise-free.Several reference color images corrupted by impulsive noise with intensities ranging from 3%to 20%are used to assess theMVDF’s effectiveness.The results of the experiments show that theMVDF is better than the VDF and the Generalized VDF(GVDF)in terms of the PSNR(Peak Signal-to-Noise Ratio),NCD(Normalized Color Difference),and execution time for the denoised image.In fact,the PSNR is increased by 6.554%and 12.624%,the NCD is decreased by 20.273%and 44.147%,and the execution time is reduced by approximately a factor of 3 for the MVDF relative to the VDF and GVDF,respectively.These results prove the efficiency of the proposed filter.Furthermore,a hardware design is proposed for the MVDF using the High-Level Synthesis(HLS)flow in order to increase its performance.This design,which is implemented on the Xilinx ZynqXCZU9EG Field-ProgrammableGate Array(FPGA),allows the restoration of a 256×256-pixel image in 2 milliseconds(ms)only.

The Spectrum of the Square of a Synchronous Random Pulse Train in Impulse Noise Environments

New forms are derived relatively simply for the spectrum of the square of synchronous randompulse train of the form , that was contaminated by impulse noise, and whose coefficient Ci areindependent, zero-mean, unit-variance random and g(t) is a given deterlninistic pulse shape. This pulsetrain's power spectrum is derived. Its discrete part can be used to synchronize carrier, and its continuouspart limits the sighal to noise ratio available in any given bandwidth irc in the spectral lines.