Inverse Filtering Research Articles

Image Enhancement Techniques for Images at Blur Motion and Different Noises

Image restoration is an art to improve image quality by disposing of reducing the amount of noise and blurring present in the image. So it is one of the research titles of interest to the researchers. The images get degraded due to environmental conditions and atmospheric difference, it is therefore important to retrieve original images using different algorithms of image processing. There are widespread applications to restore images in our world today. In this research we present a new proposed method to manipulate image using median filter and has also applied inverse filter to image restoration, then combining the proposed method with inverse filter. The proposed method has been evaluated and compared with inverse Filter and with the merger by using different performance with parameters to verify efficiency and performances of these methods. The experimental results on the test image will explain the capabilities of the proposed method to restored image, were the value of the image quality and PSNR (peak Signal to Noise ratio) is better compared with inverse filter, where values of PSNR for Lena Image is 70.3536 and for Girl Image is 71.5410 when using the proposed method of median filter, while values of PSNR when using inverse filter are 62.3225 and 62.6008 respectively when speckle noise.

Design of recognition and compensation system for vehicle communication signal based on vehicle networking

A vehicle communication signal recognition and compensation system based on vehicle network is proposed to overcome the problems of the traditional vehicle communication signal recognition system, such as poor anti-interference and signal recognition accuracy. The hardware part of the system consists of three modules. The software uses inverse operator and Wiener filter to compensate the vehicle communication signal and improves the precision of signal recognition. The MFCC parameters are extracted as the main parameters of signal recognition, and the distance measurement between the unknown communication signal and each template is obtained by using the non-linear registration mode DTW, so as to realise the optimal registration mode of signal pattern recognition. Experimental results show that the anti-interference performance of the system is about 110 dB, and the recognition rate of different types of signals is more than 85%, which proves that the system has high recognition accuracy and strong anti-interference ability.

Measurement of the Acoustic Reflection Coefficient of Materials Based on Signal Subspace Decomposition Using a Single Vector Hydrophone

A method is presented for measuring the reflection coefficient of underwater acoustic materials in the free field with a single vector hydrophone. The main advantage of this method is that the incident and reflected signals are separated in the signal subspace without considering the aliasing of direct and reflected signals in the time domain. The postprocessing inverse filter technology is introduced into the measurement. The signal distortion caused by the transfer function of the measurement system is compensated for the postprocessing inverse filter, which is conducive to eliminating the interference of the edge diffraction. The basic mechanism is based on signal subspace decomposition and postprocessing inverse filter technology. Numerical simulations are presented to demonstrate the advantages of the method. The findings are confirmed by an underwater experiment conducted with a single vector hydrophone. The experimental results show that a satisfactory reflection coefficient can be obtained using this method, and the results agree well with the numerical predictions. The relative error of the measurement results is no more than 20%.

Enhancement of Matched Filter Response for Chirp Radar Signals using Signal Recovery Technique

The matched filter is one among many effective techniques used to maximize the signal –to- noise ratio (SNR) of chirp radar signals. Besides this enhancement in SNR, it has a drawback due to sidelobe levels which degrade the filter response. There are many additional techniques which reduce these levels such as window techniques and inverse filter. In this paper, a new approach is utilized to completely cancel the level of matched filter side lobes based on the signal recovery of the compressive sensing (CS) theory. The reconstruction process of CS is based on the CAMP algorithm which applied to the response of the matched filter. The recovered chirp radar signals are achieved with completely side lobes cancellation compared to the traditional side lobe reduction technique based on the widow method. The comparison between the proposed and traditional methods is achieved according to the detection performance using Receiver Operating Characteristic (ROC) curve. Besides the detection performance, a resolution in the range is another comparison aspect between these algorithms.

Simultaneous Estimation of Glottal Source Waveforms and Vocal Tract Shapes from Speech Signals Based on ARX-LF Model

Estimating glottal source waveforms and vocal tract shapes is typically done by processing the speech signal using an inverse filter and then fitting the residual signal using the glottal source model. However, due to source-tract interactions, the estimation accuracy is reduced. In this paper, we propose a method to estimate glottal source waveforms and vocal tract shapes simultaneously based on an analysis-by-synthesis approach with a source-filter model constructed of an Auto-Regressive eXogenous (ARX) model and the Liljencrants-Fant (LF) model. Since the optimization of multiple parameters makes simultaneous estimation difficult, we first initialize the glottal source parameters using the inverse filter method, and then simultaneously estimate the accurate parameters of the glottal sources and the vocal tract shapes using an analysis-by-synthesis approach. Experimental results with synthetic and real speech signals showed that the proposed method has higher estimation accuracy than using the inverse filter.

A raypath-consistent receiver correction in PS converted wave processing through seismic interferometry: New application for tropical zones

The estimation of static corrections is an issue still unsolved for PS converted wave processing. Due to the PS converted wave usually arriving at the surface at non-zero angles, the surface consistent approach is no longer valid, and corrections become non-stationary, i.e. the correction is not static. Seismic interferometry is used in receiver gathers transformed to the radial domain to estimate functions that contain the delay caused by the weathered layer, considering the emergence angle of the PS converted wave. Inverse filters, derived from these functions, are applied by convolution to the raw traces to supply traces corrected for weathering layer effects. Seismic interferometry was satisfactorily tested in two synthetic models and then applied to a 2C seismic line from the Llanos Basin (Colombia). This is the first application of the technique in Colombia, initially developed for permafrost zones, with different assumptions and surface complexity; and it resulted in an improved PS converted wave image.

Multi-Class Random Matrix Filtering for Adaptive Learning

Covariance matrix estimation is a crucial task in adaptive signal processing applied to several surveillance systems, including radar and sonar. In this paper we propose a dynamic learning strategy to track both the covariance matrix of data and its structure (class). We assume that, given the class, the posterior distribution of the covariance is described through a mixture of inverse Wishart distributions, while the class evolves according to a Markov chain. Hence, we devise a novel and general filtering strategy, called multi-class inverse Wishart mixture filter, able to capitalize on previous observations so as to accurately track and estimate the covariance. Some case studies are provided to highlight the effectiveness of the proposed technique, which is shown to outperform alternative methods in terms of both covariance estimation accuracy and probability of correct model selection. Specifically, the proposed filter is compared with class-clairvoyant covariance estimators, e.g., the maximum likelihood and the knowledge-based recursive least square filter, and with the model order selection method based on the Bayesian information criterion.

Deconvolution for Enhancement of Biological Images Obtained by Fluorescence Microscopy

Intricate details of cells and tissues can be visualised by fluorescence microscopy and the images obtained can be then be quantitatively analysed. However, during image acquisition, distortions of the images occur by convolving the object with Point Spread Function. To remove this blurring, computational deconvolution methods are used in which the original image is restored with improved contrast. Our study analysed various fluorescence images, after the nuclei segmentation of the images, by both Deblurring (Blind Deconvolution, Lucy Richardson and Wiener filtering) and Restoration algorithms (Inverse filtering and Regularised filtering), which are the two main categories of deconvolution methods, in MATLAB 2016b. After statistical analysis (Mann Whitney U test) of area and homogeneity of the segmented nuclei of the various images for the different deconvolution methods, statistical significant difference was found in the case of area ((p=0.027) for Original vs. Inverse filter and (p=0.029) for Original vs. Regularised filter)) for restoration algorithms and for homogeneity, it was found for original vs. all the deconvolution methods, which shows that quantitative evaluation of the features can be used to further determine the better deconvolution method and in this case Restoration algorithms proves better than Deblurring algorithms.

Multifunction Filter/Inverse Filter Configuration Employing CMOS CDBAs

A voltage-mode (VM) multifunction configuration for the realization of conventional active filters and inverse active filters (IAF) using two current differencing buffered amplifiers and six passive elements has been presented. The proposed structure can realize low pass filter/inverse low pass filter (LPF/ILPF), high pass filter /inverse high pass filter (HPF/IHPF), and band pass filter/ Inverse band pass filter (BPF/IBPF) from the same circuit topology by appropriate choice(s) of the branch impedance(s). PSPICE simulations with CMOS current differencing buffered amplifiers implemented in 0.18μm CMOS TSMC technology have been presented to establish the workability of the proposed circuit configuration.

Iterative Learning of Dynamic Inverse Filters for Feedforward Tracking Control

A novel method to construct dynamic inversion compensation is proposed for feedforward tracking control. In contrast to common approaches involving parametric system identification followed by inversion synthesis, in this article we apply iterative learning control to track an impulse signal, where the converged control input is directly used to construct the inverse filter. The method is applicable to multivariable systems without a diagonalization process. The proposed method is implemented on a linear motor and an active magnetic bearing system, respectively. The experimental results are presented to demonstrate the feedforward tracking performance.

Multichannel Sparse Blind Deconvolution on the Sphere

Multichannel blind deconvolution is the problem of recovering an unknown signal $f$ and multiple unknown channels $x_{i}$ from their circular convolution $y_{i}=x_{i} \circledast f$ ( $i=1,2, {\dots },N$ ). We consider the case where the $x_{i}$ ’s are sparse, and convolution with $f$ is invertible. Our nonconvex optimization formulation solves for a filter $h$ on the unit sphere that produces sparse output $y_{i}\circledast h$ . Under some technical assumptions, we show that all local minima of the objective function correspond to the inverse filter of $f$ up to an inherent sign and shift ambiguity, and all saddle points have strictly negative curvatures. This geometric structure allows successful recovery of $f$ and $x_{i}$ using a simple manifold gradient descent (MGD) algorithm. The same approach is also applicable to blind gain and phase calibration with a Fourier sensing matrix. Our algorithm and analysis require fewer assumptions than previous algorithms for the same problem. Our theoretical findings are complemented by numerical experiments, which demonstrate superior performance of the proposed approach over the previous methods. Empirically, our algorithm has low computation cost (converging in a small number of iterations) and low memory footprint (solving only for the inverse filter of $f$ ).

Modelling Of Transport And Capture Of Particles In A Porous Medium

The study of the transport and capture of particles moving in a fluid flow in a porous medium is an important problem of underground hydromechanics, which occurs when strengthening loose soil and creating watertight partitions for building tunnels and underground structures. A one-dimensional mathematical model of long-term deep filtration of a monodisperse suspension in a homogeneous porous medium with a dimensional particle retention mechanism is considered. It is assumed that the particles freely pass through large pores and get stuck at the inlet of small pores whose diameter is smaller than the particle size. The model takes into account the change in the permeability of the porous medium and the permissible flow through the pores with increasing concentration of retained particles. A new spatial variable obtained by a special coordinate transformation in model equations is small at any time at each point of the porous medium. A global asymptotic solution of the model equations is constructed by the method of series expansion in a small parameter. The asymptotics found is everywhere close to a numerical solution. Global asymptotic solution can be used to solve the inverse filtering problem and when planning laboratory experiments.

FPGA‐based reconfigurable matrix inversion implementation for inverse filtering of multi‐channel SAR imaging

FPGA‐based reconfigurable matrix inversion implementation for inverse filtering of multi‐channel SAR imaging

Signal Processing for Enhancing Impulsiveness Toward Estimating Location of Multiple Roller Defects in a Taper Roller Bearing

Abstract Rolling element defect identification is a difficult task. The reason being that defect on the rolling element has both rotational as well as revolutionary motion. To identify rolling element defect in a taper roller bearing, a novel signal processing scheme is proposed which results in a substantial increase in kurtosis and impulse factor of the vibration signal. The scheme constitutes a series of operations. In the beginning, the raw signal is decomposed by ensemble empirical mode decomposition (EEMD) and inverse filtering (INF). The above two stages of signal processing extract hidden impulses which are suppressed in the noise present in the experimental data. In the third stage of processing, continuous wavelet transform (CWT) using adaptive wavelet is applied to the preprocessed signal to produce a 2D map of the CWT scalogram. This transformation results in a higher coefficient in the region of impulse produced due to the defect. Finally, time marginal integration (TMI) of the CWT scalogram is carried out for defect localization. The defect frequency was evaluated with an accuracy of 97.81% and defect location was identified with an accuracy of 92%.

Sound absorption coefficient measurement by extracting the first reflected wave in a short tube

This study presents a method for measuring the normal incident sound absorption coefficients of acoustic materials by extracting the first reflected wave in a short pulse tube. Instead of generating a short pulse in a tube with an open end, the inverse filter method is used when a sample is added at the end of the tube, which makes it possible to extract the first reflected wave directly from the superposed sound field in the time domain. The length of the tube used in this proposed pulse separation method is half as long as that of the traditional pulse separation method, which makes it can be used in a general commercial impedance tube. Two different materials are investigated. When the proposed method is compared to the traditional transfer function method and the traditional pulse separation method, good agreement can be observed among these three methods.

Two-dimensional complex shear modulus imaging of soft tissues by integration of Algebraic Helmoltz Inversion and LMS filter into dealing with noisy data: a simulation study.

Elasticity and viscosity of soft tissues can be obtained from the complex shear modulus imaging (CSMI). CSMI is often used not only to investigate the structure of tissues but also to detect tumors in tissues. One of the most popular ways to categorize the methods used in CSMI is into quasi-static and dynamic methods. In the dynamic method, a force excitation is used to create the shear wave propagation, and the particle velocities are measured to extract their amplitude and phase at spatial locations. These parameters are then employed to directly or indirectly estimate the Complex Shear Modulus (CSM) represented by elasticity and viscosity. Algebraic Helmholtz Inversion (AHI) algorithm provides the direct estimation of CSM using the Finite Difference Time Domain (FDTD) technique. The limitation of this method, however, is that the noise generated from measuring the particle velocity strongly degrades the accuracy of the estimation. To overcome this problem, we proposed in this paper an adaptive AHI (AAHI) algorithm that offers a good performance in CSMI with a mean error of 2.06%.

Performance Evaluation of a 40-mN Hall Thruster Using Laser-Induced Flourescence With Comprehensive Error Analysis

The laser-induced fluorescence (LIF) diagnostic with highly saturated stimulation scheme was conducted to investigate the propulsion performance of a Hall thruster. A Gaussian inverse filter was employed to isolate the Doppler shift and broadening from a measured LIF spectrum by deconvolution. Besides the average velocity and temperature of the singly ionized Xe, parameters about the overall propulsion performance were also evaluated in this work, which indicates a relatively ideal working state with average ion efficiency for acceleration above 60%, comprehensive average velocity of 18 950 m/s, plume divergence angle of 37.26° and ionization degree of 83%. In addition, error analysis in the LIF measurement was conducted quantitatively and detailedly from different aspects, which is not included in previous research. Results show that the average velocity precision is rather high with a high-quality signal, typically with a relative error about 0.64% under the signal SNR 43.96 dB. Especially, the error by laser output fluctuation can be remarkably restrained by a highly saturated stimulation scheme in this article.

Passive guided wave tomography for structural health monitoring.

In this paper the authors present a baseline-free quantitative method for imaging corrosion flaws in thin plates. It only requires an embedded guided wave sensor network used in a fully passive way, i.e., without active emission of waves. This method is called passive guided wave tomography. The aim of this development is the use of this method for the structural health monitoring of critical structures with heavy limitations on both sensor's intrusiveness and diagnostic's reliability because it allows the use of sensors that cannot emit elastic waves such as fiber Bragg gratings, which are less intrusive than piezoelectric transducers. The idea consists in using passive methods in order to retrieve the impulse response from elastic diffuse fields-naturally present in structures-measured simultaneously between the sensors. In this paper, two passive methods are studied: the ambient noise cross-correlation and the passive inverse filter. Once all the impulse responses between the sensors are retrieved, they are used as input data to perform guided wave tomography.

Research and Compensation of Frequency Response of LiNbO3 Phase Modulator for High-Performance Fiber-Optic Gyroscope

A lithium niobate (LN) phase modulator is widely spread because ofhigh electro-optic coefficients. Particularly, it is a highly required component for a closed-loop fiber-optic gyroscope (FOG) of navigation and tactical grade. However, low-frequency distortions of LN phase modulator frequency response can degrade the FOG performance. This paper deals with the research and compensation of frequency response of an LN phase modulator. It is a complex task to measure the response of the LN phase modulator in a FOG because of its Sagnac interferometer. Therefore, the special and novel modulation/demodulation algorithm is proposed. To the best of our knowledge and belief, the proposed method is the first published method that provides the measurement of the pulse response of a phase modulator as a part of a closed-loop FOG. The pulse response obtained in the proposed way allows getting appropriate high order transfer function of a phase modulator. For the first time to the best of our knowledge, the humidity dependence of the LN phase modulator frequency response is found. Influence of the phase modulator frequency response on FOG angular random walk, bias drift, and scale factor nonlinearity and instability is theoretically analyzed and mathematically simulated. The algorithmic method of the phase modulator response compensation is proposed and experimentally confirmed. The experimental results show that the proposed measurement technique of the phase modulator transfer function allows creating the compensating inverse filter that provides phase modulator response being close to flat. The application of the proposed method in the FOG operating mode allows reducing unwanted spikes to the noise level.

The Reflection Coefficients Measurement Method for the Underwater Acoustic Materials Based on the Single Vector Hydrophone

In order to obtain the normal acoustic reflection coefficients of underwater acoustic materials in the free field with the wideband pulse signal, a new measuring method with a single vector hydrophone and the post-processing inverse filtering is put forward. Numerical simulations had been conducted to comparatively analyze the measurement performances of the measuring method. The simulation results show that the present method should be established on the high ratio of signal to the noise and it is not sensitive to the system error. The experiment result shows that the post-processing inverse filtering measuring method is more effective comparing with the method without the post-processing inverse filtering, especially the measurement consequence of the post-processing inverse filtering measurement method tends to the theoretical value when the frequency is higher than 2.5 kHz, because limitation of the transducer.