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13th IEEE International Conference on Signal processing and Communication Systems (ICSPCS)

作者： Kapinchev, Konstantin Bradu, Adrian Podoleanu, Adrian Univ Kent Sch Comp Sch Phys Sci Canterbury Kent England Univ Kent Appl Opt Grp Sch Phys Sci Canterbury Kent England

ISBN: (纸本)9781728121949

This paper reviews established and emerging parallel technologies, which are employed to enhance the performance of digital signal processing algorithms. Special attention is paid to algorithms with applications in medical imaging. parallel implementations of some of the most commonly used algorithms, such as Fourier transforms, convolution and cross-correlation are discussed. parallel optimization of a newly introduced method in optical coherence tomography is presented. Its performance, in terms of latency, is presented and discussed.

关键词： parallel computing digital signal processing medical imaging optical coherence tomography

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An OpenMP-based parallel implementation of image enhancement technique for dark images

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SIGNAL IMAGE AND VIDEO processing 2024年第5期18卷 4115-4130页

作者： Hangun, Batuhan Bayar, Salih Yildiz Tech Univ Dept Comp Engn TR-34220 Istanbul Turkiye Marmara Univ Dept Elect & Elect Engn TR-34854 Istanbul Turkiye

Image enhancement is frequently used to improve the input image's visual quality. Experts also utilize image enhancement as a preprocessing method rather than a complete solution in computer vision applications. In addition, consumers want to acquire digital images with good real-life contrast, which balances the number of pixels with darker and brighter intensity values. Unfortunately, acquired images become too dark or bright to inspect visually due to bad lighting or unwanted reflections. These undesired images may cause problems in applications such as medical imaging, satellite imagery, or UAV imaging. Therefore, this study introduces an image enhancement method using local and global enhancements to overcome the above-mentioned issues. Besides image quality, there is another problem with image processing applications, such as image size. As the image size gets larger, computers usually take much more time to complete the given task. parallel computing is a method that takes advantage of several processing units on the same system using some libraries or APIs. Since it is easy to use and requires fewer sequential code changes, we preferred to use OpenMP in this study to parallelize sequential implementation. Although the proposed work is developed in C++ and is based on a small sample of dark images, the findings suggest that proposed parallel implementations can be very efficient and feasible in other programming languages for different types of image processing operations. Then, we compared the performance of both sequential and parallel implementations. Based on the experimental results, we observed that the proposed parallel implementation of the reference algorithm runs up to 38 times faster than the sequential version on a cloud computing platform with 48 physical cores.

关键词： Digital image processing parallel computing High-performance computing OpenMP

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A 3-D parallel Method of PSTD-Based Reverse Time Migration of GPR Data

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2025年 18卷 7281-7289页

作者： Huang, Lingjia Ma, Bowen Huang, Qinghua Peking Univ Sch Earth & Space Sci Beijing 100871 Peoples R China Peking Univ State Key Lab Earthquake Dynam & Forecasting Beijing 100871 Peoples R China

Ground penetrating radar (GPR) is a nondestructive technique with broad applications. Reverse time migration (RTM) of GPR data plays an important role in imaging complex structure. However, the three-dimensional (3-D) RTM of GPR data still faces big challenge due to its expensive computation cost. In this article, we develop a novel RTM method based on a 3-D parallel pseudospectral time domain (PSTD) algorithm. We apply our new RTM method to the synthetic fault model. Testing results based on the above synthetic GPR data indicate that the new RTM method is robust and effective in imaging various anomalies including faulting and layered structure. We further validate our new method based on the field GPR data across an active fault. The results demonstrate its effectivity in imaging active fault from the field data. Numerical tests also show quantitatively that the computation time and efficiency of the proposed parallel PSTD-based RTM method are significantly superior to those of the RTM algorithm based on the popular parallel finite difference time domain (FDTD) method. Comparing to the FDTD-based method, our PSTD-based method can significantly weaken the numerical dispersion effects and enhance the imaging resolution. The above superiority in computation efficiency and imaging robustness demonstrates that our new method has great potential in broadening the GPR applications, especially the cases for quasi-real-time detection and complex structure imaging.

关键词： Geophysical signal processing ground penetrating radar (GPR) pseudospectral time domain (PSTD) reverse time migration (RTM) Geophysical signal processing ground penetrating radar (GPR) pseudospectral time domain (PSTD) reverse time migration (RTM)

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Improving the magnetic resonance images super-resolution with a dual-channel enhancement model incorporating complementary information

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ENGINEERING applications OF ARTIFICIAL INTELLIGENCE 2025年 148卷

作者： He, Chunqiao Liu, Hang Shen, Yue Zhou, Deyin Wu, Lin Ma, Hailin Zhang, Tao Univ Elect Sci & Technol China Sch Life Sci & Technol Key Lab Neuroinformat Minist Educ Chengdu 611731 Peoples R China High Field Magnet Resonance Brain Imaging Lab Sich Chengdu 611731 Peoples R China Tibet Univ Plateau Brain Sci Res Ctr Lhasa 850000 Xizang Peoples R China

Although significant progress has been made in image super-resolution using artificial intelligence, achieving high-quality super-resolution for magnetic resonance (MR) images remains challenging due to their unique imaging principles and processes. Inspired by MR parallel imaging, we propose a novel concept to improve the MR image super-resolution quality by leveraging the complementary spatial information inherently contained in multi-channel receive coils. Anew MR image degradation model was developed to generate the training dataset that complies with the parallel imaging and Sensitivity Encoding (SENSE) reconstruction. A dual- channel enhancement model, named sensitivity encoding based super-resolution (SenseSR), is then devised with the main channel processing the single low-resolution image and the enhancement channel processing the multiple images from each coil channel. SenseSR is mainly featured with cascaded double enhancement blocks that can extract deeper features of the multiple coil-channel images and fuse them together into the main channel. Experiments were performed to test the performance and compare it with other benchmark models. The results demonstrate a significant improvement in MR image super-resolution quality, with an enhancement of peak signal-to-noise ratio ranging from 0.5 to 6.5 decibels (dB). Further experiments with different testing datasets and MR images collected in-situ demonstrated that SenseSR also has good generalization capability and robustness, indicating its potential for clinical applications. The code is available at https://***/MISRLab/SenseSR.

关键词： Artificial intelligence Multi-channel receive coil Magnetic resonance imaging parallel imaging Super-resolution reconstruction

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A Hardware Accelerator for Contour Tracing in Real-Time imaging

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IEEE SENSORS JOURNAL 2024年第18期24卷 29156-29166页

作者： Gupta, Sonal Goel, Shubh Kumar, Ayush Kar, Subrat IIT Delhi Dept Elect Engn New Delhi 110016 India

Contour tracing is a critical technique in image analysis and computer vision, with applications in medical imaging, big data analytics, machine learning, and robotics. We introduce a novel hardware accelerator based on the adapted and segmented (AnS) vertex following (VF) and run-data-based-following (RDBF) families of fast contour tracing algorithms implemented on the Zynq-7000 field-programmable gate array (FPGA) platform. Our algorithmic implementation utilizing a mesh-interconnected multiprocessor architecture is at least 55x faster than the existing implementations. With input-output overheads, it is up to 12.5x faster. Our hardware accelerator for contour tracing is benchmarked on mesh-interconnected hardware, all three families of contour tracing algorithms, and a random image from the Imagenet database. Our implementation is, thus, faster for FPGA, application-specific integrated circuit (ASIC), graphics processing unit (GPU), and supercomputer hardware in comparison to the central processing unit (CPU)-GPU collaborative approach and offers a better solution for those systems where the input-output overheads can be minimized, such as parallel processing arrays and mesh-connected sensor networks.

关键词： Accelerated contour tracing field-programmable gate array (FPGA) graphics processing unit (GPU) image processing multiprocessors parallel algorithms parallel processing array torus

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GPU-accelerated parallel image reconstruction strategies for magnetic particle imaging

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PHYSICS IN MEDICINE AND BIOLOGY 2024年第13期69卷 135005-135005页

作者： Quelhas, Klaus N. Henn, Mark-Alexander Farias, Ricardo Tew, Weston L. Woods, Solomon, I NIST Phys Measurement Lab Gaithersburg MD 20899 USA Univ Fed Rio de Janeiro Syst Engn & Comp Sci Program Rio De Janeiro Brazil NIST Informat Technol Lab Gaithersburg MD USA Univ Maryland Adelphi MD USA

Objective. Image reconstruction is a fundamental step in magnetic particle imaging (MPI). One of the main challenges is the fact that the reconstructions are computationally intensive and time-consuming, so choosing an algorithm presents a compromise between accuracy and execution time, which depends on the application. This work proposes a method that provides both fast and accurate image reconstructions. Approach. Image reconstruction algorithms were implemented to be executed in parallel in graphics processing units (GPUs) using the CUDA framework. The calculation of the model-based MPI calibration matrix was also implemented in GPU to allow both fast and flexible reconstructions. Main results. The parallel algorithms were able to accelerate the reconstructions by up to about 6 , 100 times in comparison to the serial Kaczmarz algorithm executed in the CPU, allowing for real-time applications. Reconstructions using the OpenMPIData dataset validated the proposed algorithms and demonstrated that they are able to provide both fast and accurate reconstructions. The calculation of the calibration matrix was accelerated by up to about 37 times. Significance. The parallel algorithms proposed in this work can provide single-frame MPI reconstructions in real time, with frame rates greater than 100 frames per second. The parallel calculation of the calibration matrix can be combined with the parallel reconstruction to deliver images in less time than the serial Kaczmarz reconstruction, potentially eliminating the need of storing the calibration matrix in the main memory, and providing the flexibility of redefining scanning and reconstruction parameters during execution.

关键词： magnetic particle imaging image reconstruction parallel computing graphical processing unit CUDA.

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Fast Atmospheric Aerosol Size and Shape imaging Instrument: Design, Calibration, and Intelligent Interaction

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2025年 74卷

作者： Dong, Li Han, Yong Hu, Maohai Zhang, Yurong Zhou, Qicheng Sun Yat Sen Univ Sch Atmospher Sci Adv Sci & Technol Space Atmospher Phys Grp ASAG Zhuhai 519082 Peoples R China Nanjing Univ Sci & Technol Sch Elect & Opt Engn Nanjing 210094 Peoples R China

Atmospheric aerosol particles have a significant impact on radiation, climate, and human health, with their size and shape being fundamental physical parameters for atmospheric change research. Due to the widespread effects and applications of aerosol particles, the direct measurement of aerosol size and shape has become crucial. Nevertheless, several challenges persist in aerosol measurement instruments, including limited resolution, complex operation, poor synchronization, and inaccurate inversion methods. Therefore, we developed a new scientific instrument and corresponding image intelligent interaction system, whose name is the fast atmospheric aerosol size and shape imaging instrument (FASI). The instrument is designed for transmission imaging that contains a light source, imaging chamber, microscope objective, tube lens, extension tube, camera, etc. Before the operation, the FASI calibrates background field, pixel size, characteristic gray value (CGV), and depth of field (DOF) based on image processing. During intelligent interaction, the FASI extracts aerosol particles by image denoising and edge detection, and then uses our proposed defocus and duplicate particle detection algorithms for secondary screening of aerosols. Aerosol size and shape parameters are measured in parallel by the central processing unit (CPU) and the graphics processing unit (GPU) using heterogeneous computation. Polystyrene latex (PSL) calculations and quantitative experiments indicate that FASI can accurately detect 0.5-20 mu m aerosol particles. In particular, the FASI measures aerosol particles supplied by an aerosol generator, dryer, and neutralizer, demonstrating that the aerosol size distribution range of oil solutions (0.5-3.5 mu m) is narrower than that of aqueous solutions (0.5-7.5 mu m). For all samples, 92.12% of aerosols have an aspect ratio (AR) exceeding 1, and the shape of these nonspherical aerosols varies greatly from each other. The evaluations of computational effici

关键词： Aerosols Particle measurements Aerosol shape aerosol size computer vision heterogeneous parallel computing intelligent instrument Aerosol shape aerosol size computer vision heterogeneous parallel computing intelligent instrument

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Ultra-high spatio-temporal resolution imaging with parallel acquisition-readout structured illumination microscopy(PAR-SIM)

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Light(Science & applications) 2024年第6期13卷 1140-1158页

作者： Xinzhu Xu Wenyi Wang Liang Qiao Yunzhe Fu Xichuan Ge Kun Zhao Karl Zhanghao Meiling Guan Xin Chen Meiqi Li Dayong Jin Peng Xi Department of Biomedical Engineering College of Future TechnologyPeking UniversityBeijing100871China Wallace H.Coulter Dept.of Biomedical Engineering Georgia Institute of Technology and Emory UniversityAtlanta30332GAUSA National Biomedical Imaging Center Peking UniversityBeijing100871China Department of Biomedical Engineering College of EngineeringSouthern University of Science and TechnologyShenzhen518055GuangdongChina Airy Technologies Co. Ltd.Beijing100086China Eastern Institute for Advanced Study Eastern Institute of TechnologyNingboZhejiang315200China School of Life Science Peking UniversityBeijing100871China Institute for Biomedical Materials and Devices(IBMD) Faculty of ScienceUniversity of Technology SydneySydneyNSW2007Australia

Structured illumination microscopy(SIM)has emerged as a promising super-resolution fluorescence imaging technique,offering diverse configurations and computational strategies to mitigate phototoxicity during real-time imaging of biological *** efforts to enhance system frame rates have concentrated on processing algorithms,like rolling reconstruction or reduced frame reconstruction,or on investments in costly sCMOS cameras with accelerated row readout *** this article,we introduce an approach to elevate SIM frame rates and region of interest(ROI)coverage at the hardware level,without necessitating an upsurge in camera expenses or intricate ***,parallel acquisition-readout SIM(PAR-SIM)achieves the highest imaging speed for fluorescence imaging at currently available detector *** using the full frame-width of the detector through synchronizing the pattern generation and image exposure-readout process,we have achieved a fundamentally stupendous information spatial-temporal flux of 132.9 MPixels·s^(−1),9.6-fold that of the latest techniques,with the lowest SNR of−2.11 dB and 100 nm ***-SIM demonstrates its proficiency in successfully reconstructing diverse cellular organelles in dual excitations,even under conditions of low signal due to ultra-short exposure ***,mitochondrial dynamic tubulation and ongoing membrane fusion processes have been captured in live COS-7 cell,recorded with PAR-SIM at an impressive 408 *** posit that this novel parallel exposure-readout mode not only augments SIM pattern modulation for superior frame rates but also holds the potential to benefit other complex imaging systems with a strategic controlling approach.

关键词： hardware illumination resolution

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Multisegment parallel Coregistration of Sentinel-1 SAR Time-Series Images by Combining OpenMP With MPI

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2025年 18卷 1656-1669页

作者： Kang, Yonghui Zhang, Yonghong Wu, Hong'an Wei, Jujie Sun, Xiaoxue Zuo, Yue Liaoning Tech Univ Sch Geomat Fuxin 123000 Peoples R China Chinese Acad Surveying & Mapping Beijing 100036 Peoples R China Beijing Guoxing Aerosp Technol Co Ltd Beijing 100196 Peoples R China

Sentinel-1 synthetic aperture radar (SAR) imagery, with its wide-swath imaging capabilities, provides crucial data for large-area interferometric SAR (InSAR) surface deformation monitoring. Precise image coregistration is essential but computationally intensive, especially for time-series processing. Current methods leveraging OpenMP for algorithm-level parallelism struggle with the large swaths and data volumes of Sentinel-1, limiting efficiency for practical applications. To address these challenges, this study introduces a multisegment parallel coregistration method combining OpenMP and MPI. The geometric coregistration process uses OpenMP and MPI for algorithm-level and multitask parallelism, boosting efficiency. In the enhanced spectral diversity coregistration, slave images are segmented by temporal baseline, with the first image processed serially and others in parallel. Validation with 30 Sentinel-1 SAR images from Tianjin-Tangshan (plain) and Zhejiang (mountainous) regions demonstrates significant improvements. OpenMP achieves optimal efficiency with 10-12 parallel kernels, while the combined OpenMP-MPI method performs best with 16 tasks for geometric coregistration and 24 for enhanced spectral diversity coregistration. The proposed method improves processing speeds by 8.2 and 6.7 times in plain regions and achieves comparable gains in mountainous areas, surpassing OpenMP alone. This approach effectively meets the efficiency demands of Sentinel-1 time-series coregistration.

关键词： Sentinel-1 parallel processing Time series analysis Main-secondary Accuracy Electrostatic discharges Diversity reception Radar polarimetry Azimuth Data processing Enhanced spectral diversity geometric coregistration multisegment parallel coregistration Sentinel-1 SAR images

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parallel Approaches to Digital Signal processing Algorithms with applications in Medical imaging

Parallel Approaches to Digital Signal Processing Algorithms ...

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International Conference on Signal processing and Communication Systems, ICSPCS

作者： Konstantin Kapinchev Adrian Bradu Adrian Podoleanu School of Computing School of Physical Sciences University of Kent Canterbury England Applied Optics Group School of Physical Sciences University of Kent Canterbury England

ISBN: (数字)9781728121949

ISBN: (纸本)9781728121956

关键词： Message systems Instruction sets Convolution Biomedical imaging Graphics processing units Signal processing algorithms Fourier transforms

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