Parallel Technologies with Image Processing Using Inverse Filter

Real-time capabilities and computational efficiency are provided by parallel image processing utilizing OpenMP. However, race conditions can affect the accuracy and reliability of the outcomes. This paper highlights the importance of addressing race conditions in parallel image processing, specifically focusing on color inverse filtering using OpenMP. We considered three solutions to solve race conditions, each with distinct characteristics: #pragma omp atomic: Protects individual memory operations for fine-grained control. #pragma omp critical: Protects entire code blocks for exclusive access. #pragma omp parallel sections reduction: Employs a reduction clause for safe aggregation of values across threads. Our findings show that the produced images were unaffected by race condition. However, it becomes evident that solving the race conditions in the code makes it significantly faster, especially when it is executed on multiple cores.

Detection of UAV Target Based on Continuous Radon Transform and Matched Filtering Process for Passive Bistatic Radar

Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration(DFM)may have a major effect due to the target maneuverability.This paper proposed an innovative long-time coherent integration approach,regarded as Continuous Radon-matched filtering process(CRMFP),for low-observable UAV target in passive bistatic radar.It not only mitigates the RM by collaborative research in range and velocity dimensions but also compensates the DFM and ensures the coherent integration through the matched filtering process(MFP).Numerical and real-life data following detailed analysis verify that the proposed method can overcome the Doppler mismatch influence and acquire comparable detection performance.

Implementation of Shock Filter for Digital X-Ray Image Processing

X-ray image might be corrupted by noise or blurring because of signal transmission or the bad X- ray lens. This paper presents a two-stage shock filter based on Partial Differential Equations (PDE) to restore noisy blurred X-ray image. Shock filters are popular morphological methods. They are used for noise removal, edge enhancement and image segmentation. Our experimental results show that the performances of shock filter are excellent in X-ray image. The peak signal-to-noise ratio (PSNR) values are 38 dB at least in restoring the noisy X-ray image. The sharpness of image’s edges increase in enhancing the blurred X-ray image. Furthermore, this paper proposes a VLSI architecture for accelerating the high-definition (HD) X-ray image (944 p) process. This paper implements the architecture in FPGA. The hardware cost is low because the computation of shock filter is low complex. To achieve the real-time processing specification, this paper uses a 5-series shock filter architecture to implement computation of HD X-ray image. This paper demonstrates a 944 p, 43.1-fps solution on 100 MHz with 133 k gate counts in Design Compiler, and with 2904 logic elements in FPGA.

An anti-aliasing filtering of quantum images in spatial domain using a pyramid structure

As a part of quantum image processing,quantum image filtering is a crucial technology in the development of quantum computing.Low-pass filtering can effectively achieve anti-aliasing effects on images.Currently,most quantum image filterings are based on classical domains and grayscale images,and there are relatively fewer studies on anti-aliasing in the quantum domain.This paper proposes a scheme for anti-aliasing filtering based on quantum grayscale and color image scaling in the spatial domain.It achieves the effect of anti-aliasing filtering on quantum images during the scaling process.First,we use the novel enhanced quantum representation(NEQR)and the improved quantum representation of color images(INCQI)to represent classical images.Since aliasing phenomena are more pronounced when images are scaled down,this paper focuses only on the anti-aliasing effects in the case of reduction.Subsequently,we perform anti-aliasing filtering on the quantum representation of the original image and then use bilinear interpolation to scale down the image,achieving the anti-aliasing effect.The constructed pyramid model is then used to select an appropriate image for upscaling to the original image size.Finally,the complexity of the circuit is analyzed.Compared to the images experiencing aliasing effects solely due to scaling,applying anti-aliasing filtering to the images results in smoother and clearer outputs.Additionally,the anti-aliasing filtering allows for manual intervention to select the desired level of image smoothness.

基于Arduino与Processing互动编程的特种仓库智能测控系统设计

基于Arduino与Processing互动编程方式进行特种仓库智能测控系统设计。该系统以Arduino为主控单元,利用各种传感器实时采集库区火情、烟雾、温度、湿度、有害气体浓度等关键参数;采用中位值平均滤波法对参数进行处理,并根据库内参数发出相应控制信号,作用于对应节点设备,实现自动控制。同时,保留人工干预措施,仓库管理人员可以根据库内环境参数做出相应的管控措施。所设计系统是集常规监测、自动控制、无人值班等功能于一体的智能化系统,对弹药、危险品、生化物品等高危物品的存储有一定的借鉴意义。

Development of a Post-Processing Automation Procedure for the GPS-Based Travel Time Data Collection Technique

The travel time data collection method is used to assist the congestion management. The use of traditional sensors (e.g. inductive loops, AVI sensors) or more recent Bluetooth sensors installed on major roads for collecting data is not sufficient because of their limited coverage and expensive costs for installation and maintenance. Application of the Global Positioning Systems (GPS) in travel time and delay data collections is proven to be efficient in terms of accuracy, level of details for the data and required data collection of man-power. While data collection automation is improved by the GPS technique, human errors can easily find their way through the post-processing phase, and therefore data post-processing remains a challenge especially in case of big projects with high amount of data. This paper introduces a stand-alone post-processing tool called GPS Calculator, which provides an easy-to-use environment to carry out data post-processing. This is a Visual Basic application that processes the data files obtained in the field and integrates them into Geographic Information Systems (GIS) for analysis and representation. The results show that this tool obtains similar results to the currently used data post-processing method, reduces the post-processing effort, and also eliminates the need for the second person during the data collection.

Elegant and Practical Method of Fir Decimation Using Comb Filters in the Field of Digital Signal Processing

This paper deals with the technology of using comb filters for FIR Decimation in Digital Signal Processing. The process of decreasing the sampling frequency of a sampled signal is called decimation. In the usage of decimating filters, only a portion of the out-of-pass band frequencies turns into the pass band, in systems wherein different parts operate at different sample rates. A filter design, tuned to the aliasing frequencies all of which can otherwise steal into the pass band, not only provides multiple stop bands but also exhibits computational efficiency and performance superiority over the single stop band design. These filters are referred to as multiband designs in the family of FIR filters. The other two special versions of FIR filter designs are Halfband and Comb filter designs, both of which are particularly useful for reducing the computational requirements in multirate designs. The proposed method of using Comb FIR decimation procedure is not only efficient but also opens up a new vista of simplicity and elegancy to compute Multiplications per Second (MPS) and Additions per Second (APS) for the desired filter over and above the half band designs.

Signal Processing Circuit Design of Infrared Detection System with SO2 Concentration Based on Correlation Filter Technology

Signals from infrared detector are very weak in SO2 concentration measuring system.In order to improve the sensitivity of detection,combining with filter correlation technology and infrared absorption principle,the weak signal processing circuit is designed according to correlation detection technology.Under laboratory conditions,system performance of SO2 concentration is tested,and the experimental data are analyzed and processed.Then relationship of SO2 concentration and the measuring voltage is provided to prove that the design improves measuring sensitivity of the system.

Digital FIR filter design for bio-signal processing system

Recently,real-time processing systems for bio-signal of the muscles generated by the movement of the user have been developed.Finite impulse response(FIR)filter for bio-signal processing in bio-signal process systems is composed of multiple multiplier and adder of high-area.This makes the chip area increase significantly.To solve this problem,a low-area digital FIR filter is proposed in this paper,which can reduce the chip area.

Pre-processing filter design at transmitters for IBI mitigation in an OFDM system

In order to meet the demands for high transmission rates and high service quality in broadband wireless communication systems, orthogonal frequency division multiplexing （OFDM） has been adopted in some standards. However, the inter-block interference （IBI） and inter-carrier interference （ICI） in an OFDM system affect the performance. To mitigate IBI and ICI, some pre-processing approaches have been proposed based on full channel state information （CSI）, which improved the system performance. A pre-processing filter based on partial CSI at the transmitter is designed and investigated. The filter coefficient is given by the optimization processing, the symbol error rate （SER） is tested, and the computation complexity of the proposed scheme is analyzed. Computer simulation results show that the proposed pre-processing filter can effectively mitigate IBI and ICI and the performance can be improved. Compared with pre-processing approaches at the transmitter based on full CSI, the proposed scheme has high spectral efficiency, limited CSI feedback and low computation complexity.

Purposeless repeated acquisition time-lapse seismic data processing

In China, most oil fields are continental sedimentation with strong heterogeneity, which on one side makes the reservoir prospecting and development more difficult, but on the other side provides more space for searching residual oil in matured fields. Time-lapse seismic reservoir monitoring technique is one of most important techniques to define residual oil distribution. According to the demand for and development of time-lapse seismic reservoir monitoring in China, purposeless repeated acquisition time-lapse seismic data processing was studied. The four key steps in purposeless repeated acquisition time-lapse seismic data processing, including amplitude-preserved processing with relative consistency, rebinning, match filtering and difference calculation, were analyzed by combining theory and real seismic data processing. Meanwhile, quality control during real time-lapse seismic processing was emphasized.

Research on Anti-noise Processing Method of Production Signal Based on Ensemble Empirical Mode Decomposition(EEMD)

The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and mechanical vibration will be mixed in the original signal, which undoubtedly will affect the prediction accuracy. Therefore, in order to reduce the influence of vibration noise on the prediction accuracy, an adaptive Ensemble Empirical Mode Decomposition(EEMD) threshold filtering algorithm was applied to the original signal in this paper: the output signal was decomposed into a finite number of Intrinsic Mode Functions(IMF) from high frequency to low frequency by using the Empirical Mode Decomposition(EMD) algorithm which could effectively restrain the mode mixing phenomenon; then the demarcation point of high and low frequency IMF components were determined by Continuous Mean Square Error criterion(CMSE), the high frequency IMF components were denoised by wavelet threshold algorithm, and finally the signal was reconstructed. The algorithm was an improved algorithm based on the commonly used wavelet threshold. The two algorithms were used to denoise the original production signal respectively, the adaptive EEMD threshold filtering algorithm had significant advantages in three denoising performance indexes of signal denoising ratio, root mean square error and smoothness. The five field verification tests showed that the average error of field experiment was 1.994% and the maximum relative error was less than 3%. According to the test results, the relative error of the predicted yield per hectare was 2.97%, which was relative to the actual yield. The test results showed that the algorithm could effectively resist noise and improve the accuracy of prediction.

Gaussian process regression-based quaternion unscented Kalman robust filter for integrated SINS/GNSS

High-precision filtering estimation is one of the key techniques for strapdown inertial navigation system/global navigation satellite system(SINS/GNSS)integrated navigation system,and its estimation plays an important role in the performance evaluation of the navigation system.Traditional filter estimation methods usually assume that the measurement noise conforms to the Gaussian distribution,without considering the influence of the pollution introduced by the GNSS signal,which is susceptible to external interference.To address this problem,a high-precision filter estimation method using Gaussian process regression(GPR)is proposed to enhance the prediction and estimation capability of the unscented quaternion estimator(USQUE)to improve the navigation accuracy.Based on the advantage of the GPR machine learning function,the estimation performance of the sliding window for model training is measured.This method estimates the output of the observation information source through the measurement window and realizes the robust measurement update of the filter.The combination of GPR and the USQUE algorithm establishes a robust mechanism framework,which enhances the robustness and stability of traditional methods.The results of the trajectory simulation experiment and SINS/GNSS car-mounted tests indicate that the strategy has strong robustness and high estimation accuracy,which demonstrates the effectiveness of the proposed method.

Structural Interpretation of Lineaments Uses Satellite Images Processing: A Case Study in North-Eastern Tunisia

This paper presents a lineament detection method using multi-band remote sensing images. The main objective of this work is to design an automatic image processing tool for lineament mapping from Landsat-7 ETM + satellite data. Five procedures were involved: 1) The Principal Component Analysis;2) image enhancement using histogram equalization technique 3) directional Sobel filters of the original data;4) histogram segmentation and 5) binary image generation. The applied methodology was contributed in identifying several known large-scale faults in the Northeast of Tunisia. The statistical and spatial analyses of lineament map indicate a difference of morphological appearance of lineaments in the satellite image. Indeed, all the lineaments present a specific organization. Five groups were classified based on three orientations: NE-SW, E-W and NW-SE. The overlapping of lineament map with the geologic map confirms that these lineaments of diverse directions can be identified and recognized on the field as a fault. The identified lineaments were linked to a deep faults caused by tectonic movements in Tunisia. This study shows the performance of the satellite image processing in the analysis and mapping of the accidents in the northern Atlas.

Evaluation of formation damages during filter cake deposition and removal process:The effect of primary damage on secondary damage

The properties of oil and gas formation could be significantly damaged during drilling and completion operations as a result of mud invasion,fluid incompatibility and interaction with rock minerals.This paper presents a systematic method for evaluating formation damage during filter cake deposition(primary damage)and removal process(secondary damage).The role of primary damage in the evolution of secondary damage was also investigated.The interaction of the filter cake solvent(chelating agent solution)with the rock samples was implemented through core flooding experiment.Nuclear Magnetic Resonance(NMR)was used to evaluate the properties of the rock sample,pre and post filter cake deposition and removal processes.The results show that secondary damaged is a strong function of the location and the intensity of the primary damage.The rock type and its pore structure also play important roles in both primary and secondary damage.The extent of secondary damage depends on the amount of barium sulphate deposited during primary damage.The chelating agent used to dissolve the barites in sandstones,deposited the barite in the small pores while it enlarges the bigger pores.In contrast,the chelating agent in the carbonate samples had multiple barite deposition points.

Unscented Transformation Based Robust Kalman Filter and Its Applications in Fermentation Process

State estimation is the precondition and foundation of a bioprocess monitoring and optimal control. However,there are many difficulties in dealing with a non-linear system,such as the instability of process, un-modeled dynamics,parameter sensitivity,etc.This paper discusses the principles and characteristics of three different approaches,extended Kalman filters,strong tracking filters and unscented transformation based Kalman filters.By introducing the unscented transformation method and a sub-optimal fading factor to correct the prediction error covariance,an improved Kalman filter,unscented transformation based robust Kalman filter,is proposed. The performance of the algorithm is compared with the strong tracking filter and unscented transformation based Kalman filter and illustrated in a typical case study for glutathione fermentation process.The results show that the proposed algorithm presents better accuracy and stability on the state estimation in numerical calculations.

IMAGE PROCESSING METHOD FOR PHOTOCARRIER SPECKLE FRINGE

In the present paper,a new image processing method for photocarrierspeckle fringe is proposed.A simple and fast filter is designed for different kinds of specklefringe with certain direction to eliminate the speckle effect.Fringe multiplication is carriedout with personal computer.The procedure of photocarrier speckle image collecting,pro-cessing,calculating and verifying is described with a practical example.

Methods of Data Processing for Trace Elements Analysis Using Laser Induced Breakdown Spectroscopy

With the development of Laser Induced Breakdown Spectroscopy （LIBS）, increasing numbers of researchers have begun to focus on problems of the application. We are not just satisfied with analyzing what kinds of elements are in the samples but are also eager to accomplish quantitative detection with LIBS. There are several means to improve the limit of detection and stability, which are important to quantitative detection, especially of trace elements, increasing the laser energy and the resolution of spectrometer, using dual pulse setup, vacuuming the ablation environment etc. All of these methods are about to update the hardware system, which is effective but expensive. So we establish the following spectrum data processing methods to improve the trace elements analysis in this paper： spectrum sifting, noise filtering, and peak fitting. There are small algorithms in these three method groups, which we will introduce in detail. Finally, we discuss how these methods affect the results of trace elements detection in an experiment to analyze the lead content in Chinese cabbage.

Controlling of crustacean zooplankton reproduction in biological activated carbon (BAC) filters by strengthen operation and management of conventional process

To counter the mass reproduction and penetration of crustacean zooplankton in Biological Activated Carbon(BAC)filters which may result in the presence of organisms in potable water and water pollution,this paper analyzed the factors affecting organisms' reproduction in BAC filters.A comparative study was performed on the density and composition of crustacean zooplankton of the concerned water treatment units of two advanced water plants(Plant A and B)which with the same raw water and the same treatment technique in southern China.The results obtained show that the crustaceans' density and composition was very different between the sand filtered water of Plant A and Plant B.which Harpacticoida bred sharply in the sediment tanks and penetrated sand filter into BAC filters was the primary reason of crustaceans reproduce in BAC filters of Plant A.For prevention of the organisms reproduction in BAC,some strengthen measures was taken including pre-chlorination,cleaning coagulation tanks and sediment tanks completely,increasing sludge disposal frequency to stop organisms enter BAC filters,and the finished water quality was improved and enhanced.

Image processing of ESPI based on measurement the welding dynamic displacement fields

A dual-beam electronic speckle pattern interferometry (ESPI) system was adopted to get speckle patterns for the measurement of welding dynamic displacement fields. The mathematical model of this system was described, based on which methods of the ESPI pattern image processing were discussed. Gray transformation and histogram equalization were used to enhance the contrast of speckle patterns. A discrete cosine image processing method was carried out and an exponent low-pass filter was chosen to reduce multiplicative noise in speckle patterns. Speckle grain noise can be eliminated effectively after these processes.