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A Bidirectional Guided Filter Used for RGB-D Maps

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2023年 72卷 1页

作者： Zhang, Ruijie Wu, Jun Tsinghua Univ State Key Lab Tribol Adv Equipment Beijing 100084 Peoples R China Tsinghua Univ Inst Mfg Engn Dept Mech Engn Beijing 100084 Peoples R China Beijing Key Lab Precis Ultraprecis Mfg Equipment & Beijing 100084 Peoples R China

The red-green-blue-depth (RGB-D) cameras are widely used in the fields of robotic spray painting, packaging, and tracking. However, the quality of the depth maps of RGB-D maps is relatively low. Guided filters utilizing the color image as a guide map is a common method to deal with these problems. However, the noise in guidance will make the filtering output contains unexpected noise that does not contain before filtering. In this article, based on the classical guided filter, a bidirectional guided filter is proposed to filter the filtering input and the guidance simultaneously. The basic equations are proposed and the filter kernel is derived. The properties of the proposed bidirectional guided filter, such as edge-preserving filtering property, insensitivity to the noise of guidance, and filtering effects on guidance, are investigated. Four different groups of experiments are performed to further verify the effectiveness of the proposed method. The classical guided filter and the bidirectional guided filter are compared to verify that the proposed bidirectional guided filter can reduce the impact of the noise of the guidance;and the bidirectional guided filter and the box mean filter are compared to verify the filtering effect on guidance of the proposed bidirectional guided filter.

关键词： Mathematical models Information filters Image edge detection Cameras Kernel filtering algorithms Robot vision systems 3-D vision edge-preserving filtering guided filter machine vision red-green-blue-depth (RGB-D) map

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Gaussian Synthesis for High-Precision Location in Oriented Object Detection

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2023年 61卷 1页

作者： Li, Zhonghua Hou, Biao Wu, Zitong Ren, Bo Ren, Zhongle Jiao, Licheng Xidian Univ Key Lab Intelligent Percept & Image Understanding Minist Educ China Xian 710071 Peoples R China Xidian Univ Joint Int Res Lab Intelligent Percept & Computat Xian 710071 Peoples R China

In aerial image scenes, the objects have properties of arbitrary orientation, large-scale range, and dense distribution. Thus, the object detector uses an oriented bounding box (OBB) to locate objects, which is more complex and challenging than a horizontal bounding box (HBB) detector. Mainstream OBB detectors mostly use a one-to-many label assignment strategy to predict multiple bounding boxes for the same object and filter out repeat predictions by nonmaximum suppression (NMS). NMS ranks with confidence and drops the detection box with intersection over union (IoU) higher than the threshold, which makes it easy to get the local optimum result. The clustered synthesis method gets more accurate results than the original NMS, but applying it to the OBB detector leads to border shift, which arises from the angular discontinuity problem. Therefore, we use Gaussian OBB (G-OBB) to deal with the angular discontinuity and thus eliminate the offset generated by direct synthesis. G-OBB is not easy to understand and describe representation. For this reason, we analyze the properties of G-OBB and design a decoding method to convert a G-OBB to a rotated rectangular box, further discussing its conditions. Based on the decoding method, we propose a Gaussian synthesis (GauS) algorithm, which transforms the OBB into Gaussian space, followed by synthesis, and finally transforms the synthesis result back into a new OBB. We have derived the synthesis and decoding methods and further verified their effectiveness. The extensive experiments on several existing models show that GauS takes very little computation and improves the detector's high-precision performance. Extensive experiments verify the effectiveness, stability, and universality of the proposed algorithm. In addition, the RTMDet using GauS achieves a performance of 81.61 AP50 and gains a 0.39% improvement in mean average precision (mAP), which achieves the state-of-the-art (SOTA) performance. Our implementation is available a

关键词： Detectors Object detection Prediction algorithms Decoding Shape Task analysis filtering algorithms Aerial object detection Gaussian synthesis (GauS) nonmaximum suppression (NMS) oriented object detection postprocess

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Joint Design of Transmit Sequence and Receive Filter Based on Riemannian Manifold of Gaussian Mixture Distribution for MIMO Radar

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2023年 61卷 1页

作者： Chen, Xixi Wu, Hao Cheng, Yongqiang Feng, Weike Guo, Yifan Air Force Engn Univ Air Def & Antimissile Sch Xian 710051 Shaanxi Peoples R China Natl Univ Def Technol Coll Elect Sci Changsha 410073 Hunan Peoples R China Northwestern Polytech Univ Sch Marine Sci & Technol Xian 710072 Shaanxi Peoples R China

To improve target detection performance in non-Gaussian backgrounds, the joint design of transmit sequence and receive filter for multiple-input-multiple-output (MIMO) radar is studied. By approximating the probability density function of observed non-Gaussian data with the Gaussian mixture model (GMM), a Riemannian manifold of Gaussian mixture distribution is developed to depict the complicated background first. Then, maximizing the geometric distance on manifolds, which is converted by maximizing the discrimination between the target and clutter, is proposed as the criterion for the joint design of transmit sequence and receive filter. Thereby, under the constant-modulus constraint, the joint design problem can be transformed into an optimization problem. However, the proposed optimization problem is nonconvex and constrained. To solve this problem, a Riemannian optimization framework is provided. By taking the advantage of the underlying geometric and algebraic structure of the constraint space, the original constrained optimization problem in Euclidean space can be transformed into the unconstraint optimization problem over Riemannian product manifolds. Moreover, to obtain the global optimal solution, the Riemannian gradient of the geometric distance cost is derived for the conjugate gradient algorithm. Experiments demonstrate that the proposed method shows advantages in detection performance compared with competitive methods.

关键词： Manifolds Optimization Clutter MIMO radar Object detection filtering algorithms filtering theory Complex circle manifold Gaussian mixture model (GMM) joint design manifold optimization matrix information geometry detection multiple-input-multiple-output (MIMO) radar product manifold

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A Novel Method for Microphone Channel Frequency Response Calibration Based on Newton Algorithm

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2023年 72卷 1页

作者： Wang, Ziyi Zhao, Zhao Xu, Zhiyong Nanjing Univ Sci & Technol Sch Elect & Opt Engn Nanjing 210094 Peoples R China

Microphone arrays are widely applied in practical applications. In an array, each channel conventionally contains an acoustic sensor and a following signal conditioning circuit (SCC). Frequency response mismatches among channels will adversely affect array's overall performance. Existing calibration methods provide promising results;however, their accuracy varies considerably across full frequency band and the passband bandwidth shrinkage problem also arises. To address these problems, we propose a novel calibration method based on Newton algorithm. The proposed method cascades calibration filters after channel output signals allowing the frequency response calibration to be equivalent to the optimization of calibration filter coefficients. First, all uncalibrated channels' bandwidths are analyzed using a chirp calibration signal, resulting in appropriate construction of the desired output. Next, a spectrum mean square error criterion between each channel output and the desired signal is utilized to formulate the frequency response mismatch. Finally, we employ Newton algorithm to design the calibration filter coefficients corresponding to each channel. Explicit mathematical derivation is provided. Since the cost function is quadratic, expressions of the constant Hessian matrix and its inverse are derived. Furthermore, the inverse Hessian can be efficiently computed using spectral coefficients of channel outputs. Simulation results reveal that the proposed method significantly outperforms the state-of-the-art calibration approaches in terms of calibration accuracy, calibrated passband bandwidth performance, and convergence rate. Real-world experiments also verify its effectiveness.

关键词： Calibration Bandwidth Frequency response Passband Loudspeakers Microphone arrays filtering algorithms Frequency response calibration microphone channel Newton algorithm

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Real Time Modeling and Control Algorithm of a Grid-Connected Battery Energy Storage System

Real Time Modeling and Control Algorithm of a Grid-Connected...

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IEEE Texas Power and Energy Conference (TPEC)

作者： Sepehr Karimi Solmaz Nazaralizadeh Anurag Srivastava Aboubakr Salem Parviz Famouri Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown USA Electrical and Computer Engineering Dept. WVU-IT Beckley USA PCS Eaton Pittsburgh PA USA

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

This work develops real time model and associate control for a grid-tied battery energy storage system (BESS), based on the real industrial system specifications, 362kW/1499kWh lithium-ion BESS. An active and reactive power controller based on the dq reference frame is designed for the grid-tied inverter. To ensure system performance, an LCL filter with passive damping is also developed and analyzed. The system is tested using the Controller Hardware-in-the-Loop (CHIL) platform: Typhoon. The results demonstrate the controller's effective reference tracking across varying load conditions, with the filter design achieving a 3.3% output current THD, emphasizing the inverter's optimized performance.

关键词： Damping Reactive power Tropical cyclones Passive filters Battery energy storage system System performance filtering algorithms Real-time systems Inverters Load modeling

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Novel Algorithm to Solve the Constrained Path-Based Testing Problem

Novel Algorithm to Solve the Constrained Path-Based Testing ...

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IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW

作者： Matej Klima Miroslav Bures Marek Miltner Chad Zanocco Gordon Fraser Sebastian Schweikl Patric Feldmeier Czech Technical University in Prague Czech Republic Stanford University California University of Passau Germany

ISBN: (数字)9798331534677

ISBN: (纸本)9798331534684

Constrained Path-based Testing (CPT) is a technique that extends traditional path-based testing by adding constraints on the order or presence of specific sequences of actions in the tests of System Under Test (SUT) processes. Through such an extension, CPT enhances the ability of the model to capture more real-life situations. In CPT, we define four types of constraints that either enforce or prohibit the use of a pair of actions in the resulting test set. We propose a novel Constrained Path-based Testing Composition (CPC) algorithm to solve the Constrained Path-based Testing Problem. We compare the results returned by the CPC algorithm with two alternatives, (1) the Filter algorithm, which solves the CPT problem in a greedy manner, and (2) the Edge algorithm, which generates a set of test cases that satisfy edge coverage. We evaluated the algorithms on 200 problem instances, with the CPC algorithm returning test sets (T) that have, on average, 350 edges, which is 2.4% and 11.1% shorter than the average number of edges in T returned by the Filter algorithm and the Edge algorithm, respectively. Regarding the compliance of the generated T with the constraints, the CPC algorithm produced T that satisfied the constraints in 95% of the cases, the Filter algorithm in 45% cases, and the Edge algorithm returned T that satisfied the constraints only for 6% SUT instances. Regarding the coverage of edges, the CPC algorithm returned test sets that contained, on average, 91.5% of edges in the graphs, while for T returned by the Filter algorithm, it was 90.8% edges. When comparing the average results of the edge coverage criterion and the fulfillment of the constraint criterion by individual algorithms, we consider the incomplete edge coverage achieved by the CPC algorithm and, at the same time, 95% fulfillment of the graph constraints to be a reasonable compromise.

关键词： Software testing Scalability Conferences Software algorithms Semantics Metaheuristics Employment Directed graphs filtering algorithms Testing

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Innovative Median Finding Algorithm for Coherent Noise Removal in High Energy Physics Experiments

Innovative Median Finding Algorithm for Coherent Noise Remov...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Nicolas Guimarães Guilherme Aniya Bruno Sanches Irakli Mandjavidze Damien Neyret Wilhelmus Van Noije Department of Electronic Systems Engineering The School of Engineering (EPUSP) São Paulo Brazil IRFU CEA Gif-Sur-Yvette France

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

Several high energy physics experiments suffer from coherent noise affecting their readout electronics. To solve that, the highly successful SAMPA chip is gaining a new successor, the SALSA front-end readout ASIC, which is going to be used in the EIC experiment of the Brookhaven National Laboratory, United States. This new integrated circuit is going to have a common mode noise subtraction, a non-linear filter that is based on finding median values between the many channels of the chip. To guarantee peak efficiency in the filter implementation, this work focuses on the filter's core: the median finder. This part needs to have an efficient algorithm to be implemented in hardware, therefore this paper shows three approaches, two of which are original techniques for digital median finding. These three designs were implemented and verified in TSMC 65nm technology and lastly they were compared in terms of speed, area, power consumption and a preliminary evaluation of error tolerance.

关键词： Integrated circuits High energy physics Power demand Circuits and systems Noise Layout filtering algorithms Hardware Digital filters Readout electronics

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Environment Perception and Spatial Localization algorithms in Virtual Reality

Environment Perception and Spatial Localization Algorithms i...

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Digital Analysis and Processing, Intelligent Computation (DAPIC), International Conference on

作者： Yetong Wang Bing Zheng Kongduo Xing Hainan Vocational University of Science and Technology Haikou Hainan China

ISBN: (数字)9798331536169

ISBN: (纸本)9798331536176

With the rapid development of virtual reality technology, environment perception and spatial localization algorithms have become an important technical foundation for improving the accuracy and inter activity of virtual experience. Environment perception mainly involves the perception and understanding of various objects and situations in the virtual environment, while spatial localization is the key technology to realize the precise positioning and action tracking of users in the virtual space. This paper reviews the research progress of environment perception and spatial localization in virtual reality, focusing on the current mainstream localization methods, including sensor-based localization technology, computer vision algorithms and their fusion technology. By analyzing the characteristics and application scenarios of various types of algorithms, the advantages and limitations of them in virtual reality are discussed. Especially in terms of multi-sensor fusion and real-time localization accuracy improvement, the paper proposes possible innovative directions. The article also discusses the role of emerging technologies, such as artificial intelligence and 5G communication, in promoting environment sensing and spatial localization algorithms, and looks forward to the future wide application in the fields of gaming, health care, and education. Significant progress has been made in current technologies, and high-precision, low-latency, and low-cost solutions remain the focus of future research.

关键词： Location awareness Accuracy Heuristic algorithms Virtual reality filtering algorithms Prediction algorithms Real-time systems User experience Sensors Kalman filters

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A Novel Implementation of a Line X-Ray Source and Its Application to Computed Tomography with Linear Scan Trajectories

A Novel Implementation of a Line X-Ray Source and Its Applic...

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IEEE International Symposium on Biomedical Imaging

作者： Daxin Shi Yu Zou Yi Yang Medichord LLC Delaware USA

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

In this work, we propose a novel implementation of a line xray source and investigate the computed tomographic (CT) image reconstruction algorithms where linear scan trajectories are assumed. In our proposal, a line x-ray source is realized by introducing a new design of an x-ray tube. Compared with the conventional x-ray tube design, the new tube contains a helical fin as the target. When incoming electrons bombard the surface of a rotating helical fin, a sequence of x-ray focal spots will be produced forming a line x-ray source. Equipped with the novel x-ray tube, x-ray CT scanners can be built where linear scan trajectories are assumed. We demonstrate also in this work that multiple linesegment scan trajectory CT reconstruction problems can be readily solved by Katsevich's filtered backprojection (FBP) algorithm.

关键词： Surface reconstruction Computed tomography Reconstruction algorithms filtering algorithms Trajectory Proposals X-ray imaging Image reconstruction Electrons Biomedical imaging

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Optimized Distributed Time Synchronization Algorithm for Wireless Sensor Networks Based on Kalman Consensus Filter

Optimized Distributed Time Synchronization Algorithm for Wir...

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Advanced algorithms and Control Engineering (ICAACE), International Conference on

作者： Duo Chen Jialong Liu Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

In this paper, a time synchronization optimization algorithm (DOKCF-PL) for distributed wireless sensor networks (WSNs) in packet loss and transmission delay environments is proposed. By developing a joint optimization strategy for optimal Kalman gain and consensus gain, the algorithm improves the robustness and convergence speed of the system while maintaining highly accurate synchronization performance. To account for the effects of packet loss and transmission delay on the synchronization performance, an equivalent observation noise processing method is proposed, which significantly improves the synchronization stability. The simulation results show that the DOKCF-PL algorithm has excellent synchronization performance under different network topologies and packet losses, confirming its potential application in dynamic network environments.

关键词： Wireless sensor networks Machine learning algorithms Heuristic algorithms Packet loss filtering algorithms Robustness Stability analysis Synchronization Kalman filters Optimization

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