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Real-Time Hyperspectral image Compression Onto Embedded GPUs

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2019年第8期12卷 2803-2820页

作者： Diaz, Maria Guerra, Raul Horstrand, Pablo Martel, Ernestina Lopez, Sebastian Lopez, Jose F. Sarmiento, Roberto Univ Las Palmas Gran Canaria Inst Appl Microelect Las Palmas Gran Canaria 35017 Spain

Real-time hyperspectral imaging on-board compression represents a critical processing step in many remote sensing applications where the acquired hyperspectral data need to be efficiently stored and/or transferred. However, the complexity of the compression algorithms as well as the volume of data to be compressed and the limited computational resources of the hardware devices available on-board turn the real-time compression into a very challenging task. This paper presents a low-power-consumption solution for real-time lossy compression of hyperspectral images. The lossy compression algorithm for hyperspectral image system (HyperLCA) compressor has been implemented onto two NVIDIA Jetson developer kits. These NVIDIA boards include low-power embedded graphic processing units, which allow parallel programing for speeding up the compression process at a reasonable low power consumption. The experiments carried out in this paper are oriented to the necessities imposed by a specific smart farming application although all drawn conclusions are extrapolable to other fields in which remotely sensed hyperspectral images are to be compressed in real time. The obtained results verify both the good performance of the HyperLCA compressor for the targeted application and the achievement of a real-time performance by using the developed implementations. Additionally, several comparisons and conclusions have been drawn from the experiments in relation to the different strategies employed for accelerating the compression process.

关键词： CUDA embedded systems hyperspectral compression lossy compression low-power graphical processing units (LPGPUs) real time unmanned aerial vehicle (UAV)

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Accelerating B-spline interpolation on GPUs: Application to medical image registration

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COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2020年 193卷 105431-105431页

作者： Zachariadis, Orestis Teatini, Andrea Satpute, Nitin Gomez-Luna, Juan Mutlu, Onur Elle, Ole Jakob Olivares, Joaquin Univ Cordoba Dept Elect & Comp Engn Cordoba Spain Oslo Univ Hosp Intervent Ctr Rikshosp Oslo Norway Univ Oslo Dept Informat Oslo Norway Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland

Background and Objective: B-spline interpolation (BSI) is a popular technique in the context of medical imaging due to its adaptability and robustness in 3D object modeling. A field that utilizes BSI is image Guided Surgery (IGS). IGS provides navigation using medical images, which can be segmented and reconstructed into 3D models, often through BSI. image registration tasks also use BSI to transform medical imaging data collected before the surgery and intra-operative data collected during the surgery into a common coordinate space. However, such IGS tasks are computationally demanding, especially when applied to 3D medical images, due to the complexity and amount of data involved. Therefore, optimization of IGS algorithms is greatly desirable, for example, to perform image registration tasks intra-operatively and to enable real-time applications. A traditional CPU does not have sufficient computing power to achieve these goals and, thus, it is preferable to rely on GPUs. In this paper, we introduce a novel GPU implementation of BSI to accelerate the calculation of the deformation field in non-rigid image registration algorithms. Methods: Our BSI implementation on GPUs minimizes the data that needs to be moved between memory and processing cores during loading of the input grid, and leverages the large on-chip GPU register file for reuse of input values. Moreover, we re-formulate our method as trilinear interpolations to reduce computational complexity and increase accuracy. To provide pre-clinical validation of our method and demonstrate its benefits in medical applications, we integrate our improved BSI into a registration work-flow for compensation of liver deformation (caused by pneumoperitoneum, i.e., inflation of the abdomen) and evaluate its performance. Results: Our approach improves the performance of BSI by an average of 6.5x and interpolation accuracy by 2 x compared to three state-of-the-art GPU implementations. Through pre-clinical validation, we demon

关键词： Medical image registration Medical image processing parallel computing GPU B-splines

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3D Volume Visualization System Based on GPUs for Medical Big Data 4th

3D Volume Visualization System Based on GPUs for Medical Big...

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4th International Conference on Big Data applications and Services ( (BigDAS)

作者： Yoon, Joseph Kown, Oh-Soek Cheong, Jae-Gyun Park, Keon-Kuk Kim, Young-Bong Pukyong Natl Univ IT Convergence & Applicat Engn Yongso Ro 45 Busan 48513 South Korea

ISBN: (纸本)9789811306952;9789811306945

With the appearance of computerization society, medical equipment has been closely coupling with computers. images from medical equipment have become very useful basic data in diagnosing the state of a patent. These images have often obtained from medical computerized equipment such as x-ray system, Ultrasound system, Computerized Tomography (CT), Magnetic Resonance imaging (MRI), and so on. For increasing the effective value of those images, we have to employ the preprocessing techniques such as a median filter, a Gaussian filter, and a mean filter. And also, we take the special algorithms such as a phase correction, a dispersion compensation, and a Hilbert transform. These additional techniques make it impossible to watch the images in a real time. Thus, we have to get a rapid processing of medical images for the real-time display of those images. In this research, we will propose a method to give a real-time display of images using multi-thread techniques and parallel processing algorithms. In a multi-thread technique, if two threads share the same resource, one thread may change the resource data during the processing of the other thread. We will design a method to avoid the collision in a resource usage right between threads.

关键词： Triple buffers Dual GPU Medical image processing 3D volume

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parallel Fast Pencil Drawing Generation Algorithm Based on GPU

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IEEE ACCESS 2019年 7卷 83543-83555页

作者： Qiu, Jiyan Liu, Bin He, Jinrong Liu, Chaoyang Li, Yuancheng Northwest A&F Univ Coll Informat Engn Yangling 712100 Shaanxi Peoples R China Northwest A&F Univ Key Lab Agr Internet Things Minist Agr & Rural Affairs Yangling 712100 Shaanxi Peoples R China Northwest A&F Univ Shaanxi Key Lab Agr Informat Percept & Intelligen Yangling 712100 Shaanxi Peoples R China Yanan Univ Coll Math & Comp Sci Yanan 712100 Peoples R China Xian Univ Sci & Technol Sch Comp Sci & Technol Xian Shaanxi Peoples R China

With the development of image processing technology, pencil drawing has been widely used in video games and mobile phone applications. However, the existing pencil drawing algorithms require a large amount of time to convert a real picture into a pencil drawing;hence, it is difficult to apply them to real-time systems. This paper proposes a parallel fast pencil drawing generation algorithm based on the graphics processing unit (GPU) to accelerate the real-time rendering process of sketch painting. The parallelism of the pencil drawing generation algorithm is identified via a theoretical analysis at first. Then, sub-algorithms of the sequential algorithm are designed in parallel using the compute unified device architecture (CUDA) programming model and executed via thread-level parallel techniques. Furthermore, an optimal cache pattern of data that reduce the access time of the most frequently used data is structured using shared memory and constant memory. Finally, task-level parallelism is achieved by the CUDA stream technology, which overlaps independent sub-tasks for further acceleration. On the CUDA platform, the experimental results demonstrate that the proposed parallel algorithm can achieve a significant increase in speedup. The proposed algorithm achieves a performance improvement of 448.59 times compared with the sequential algorithm, on 2560 x 1920-resolution images, and maintains a high degree of similarity with the real pencil paintings. Hence, the proposed algorithm is suitable for real-time pencil drawing rendering and has promising application prospects in non-photorealistic rendering.

关键词： Non-photorealistic rendering pencil drawing parallel algorithm GPU platform convolution operation CUDA

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Map-Reduce based tipping point scheduler for parallel image processing

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ExPERT systems WITH applications 2020年 139卷 112848-000页

作者： Akhtar, Mohammad Nishat Saleh, Junita Mohamad Awais, Habib Abu Bakar, Elmi Univ Sains Malaysia Sch Aerosp Engn Nibong Tebal 14300 Penang Malaysia Univ Sains Malaysia Sch Elect & Elect Engn Nibong Tebal 14300 Penang Malaysia

Nowadays, Big Data image processing is very much in need due to its proven success in the field of business information system, medical science and social media. However, as the days are passing by, the computation of Big Data images is becoming more complex which ultimately results in complex resource management and higher task execution time. Researchers have been using a combination of CPU and GPU based computing to cut down the execution time, however, when it comes to scaling of compute nodes, then the combination of CPU and GPU based computing still remains a challenge due to the high communication cost factor. In order to tackle this issue, the Map-Reduce framework has come out to be a viable option as its workflow optimization could be enhanced by changing its underlying job scheduling mechanism. This paper presents a comparative study of job scheduling algorithms which could be deployed over various Big Data based image processing application and also proposes a tipping point scheduling algorithm to optimize the workflow for job execution on multiple nodes. The evaluation of the proposed scheduling algorithm is done by implementing parallel image segmentation algorithm to detect lung tumor for up to 3GB size of image dataset. In terms of performance comprising of task execution time and throughput, the proposed tipping point scheduler has come out to be the best scheduler followed by the Map-Reduce based Fair scheduler. The proposed tipping point scheduler is 1.14 times better than Map-Reduce based Fair scheduler and 1.33 times better than Map-Reduced based FIFO scheduler in terms of task execution time and throughput. In terms of speedup comparison between single node and multiple nodes, the proposed tipping point scheduler attained a speedup of 4.5 x for multi-node architecture. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Job scheduler Workflow optimization Map-Reduce Tipping point scheduler parallel image segmentation Lung tumor

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FPGA implementation of SAR Bi-Channel synthesis based on inverse filtering

FPGA implementation of SAR Bi-Channel synthesis based on inv...

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IET International Radar Conference (IET IRC 2020)

作者： x. Shao H. Shi L. Chen N. Zhang Beijing Institute of Technology Beijing China

In a multi-channel synthetic aperture radar (MSAR) system, non-uniform azimuth sampling is an important factor affecting imaging. If it is not processed and then imaged directly, it will inevitably lead to deterioration of imaging performance. The channel synthesis algorithm based on inverse filtering is a method to solve this problem. However, in actual applications, it is necessary to perform specific optimization processing on the algorithm to meet real-time requirements. This paper designs a new architecture for efficient implementation of channel synthesis algorithms. The design makes full use of the parallel characteristics of FPGA to improve the speed of the algorithm. By optimizing the DDR read-write control logic, the data transfer rate is improved. Finally, the Modelsim software is used to obtain the simulation results. At 150 MHz,the processing speed could reach 461.6MSamples/s (64bit/sample).

关键词： field programmable gate arrays synthetic aperture radar radar imaging image filtering image sampling optimisation

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3D/4D hybrid spectral domain synthetic aperture image reconstruction method for hand-held ultrasound systems

3D/4D hybrid spectral domain synthetic aperture image recons...

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IEEE International Ultrasonics Symposium (IUS)

作者： Tasinkevych, Yuriy Lewandowski, Marcin Walczak, Mateusz Inst Fundamental Technol Res PAS Dept Ultrasound Warsaw Poland

ISBN: (纸本)9781728145969

In the last few decades 3D/4D ultrasonography has been gaining increasing popularity not only as a scientific research topic but also as a new modality of medical imaging in clinical applications. However, design and implementation of 3D/4D device for high quality ultrasound imaging within portable, hand-held systems is a technological challenge. Design of transmit/receive (Tx/Rx) electronics for efficient operation with 2D array transducers, comprised of thousands of elements, enormous amount of input/output data that must be transferred and processed, power consumption limitation are just a few of the difficulties that arise. No less important is development of reliable and numerically efficient algorithms for 3D/4D imaging which should take all these restrictions into account. The main objective of this paper is to present a new hybrid spectral domain imaging (HSDI) method that delivers an original and innovative solution for the technical limitations of modern ultrasonography 3D/4D. The developed image reconstruction method is based on the plane-wave insonification (PWI) with sub-aperture data acquisition combined with frequency domain (FD) data processing. The performance of the method was tested using the Field ii simulated acoustic data of 3D cyst phantom. For a 3D low-resolution image (LRI) comprised of 64x64x512 pixels the proposed HSDI method is about 100 times faster, in the case of a single 3D, than its counterpart based on the PWI synthetic aperture time domain (TD) method for a single Tx/Rx event. On the other hand, the frame rate increase is proportional to the number of sub-apertures used for a single high-resolution image (HRI) synthesis

关键词： ultrasonography Fourier domain beamforming time domain beamforming plane wave imaging sub-aperture data acquisition

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Architecture-Centric Bottleneck Analysis for Deep Neural Network applications 26

Architecture-Centric Bottleneck Analysis for Deep Neural Net...

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26th International Conference on High Performance Computing, Data and Analytics (HiPCW)

作者： Ryoo, Jihyun Fan, Mengran Tang, xulong Jiang, Huaipan Arunachalam, Meena Naveen, Sharada Kandemir, Mahmut T. Penn State Univ State Coll PA 16801 USA Intel Mountain View CA USA

ISBN: (纸本)9781728145358

The ever-growing complexity and popularity of machine learning and deep learning applications have motivated an urgent need of effective and efficient support for these applications on contemporary computing systems. In this paper, we thoroughly analyze the various DNN algorithms on three widely used architectures (CPU, GPU, and xeon Phi). The DNN algorithms we choose for evaluation include i) Unet - for biomedical image segmentation, based on Convolutional Neural Network (CNN), ii) NMT - for neural machine translation based on Recurrent Neural Network (RNN), iii) ResNet-50, and iv) DenseNet- both for image processing based on CNNs. The ultimate goal of this paper is to answer four fundamental questions: i) whether the different DNN networks exhibit similar behavior on a given execution platform? ii) whether, across different platforms, a given DNN network exhibits different behaviors? iii) for the same execution platform and the same DNN network, whether different execution phases have different behaviors? and iv) are the current major general-purpose platforms tuned sufficiently well for different DNN algorithms? Motivated by these questions, we conduct an in-depth investigation of running DNN applications on modern systems. Specifically, we first identify the most time-consuming functions (hotspot functions) across different networks and platforms. Next, we characterize performance bottlenecks and discuss them in detail. Finally, we port selected hotspot functions to a cycle-accurate simulator, and use the results to direct architectural optimizations to better support DNN applications.

关键词： DNN CPU GPU xeon Phi Characterization

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Dual charge-coupled device (CCD), astronomical spectrometer and direct imaging camera ii. Data handling and control systems

Dual charge-coupled device (CCD), astronomical spectrometer ...

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applications of Digital image processing to Astronomy 1980

作者： Dewey, D. Ricker, G.R. Massachusetts Institute of Technology Department of Physics Center for Space Research Room 37-527 77 Massachusetts Avenue CambridgeMA02139 United States

The data collection system for the MASCOT (MIT Astronomical Spectrometer/Camera for Optical Telescopes) is described. The system relies on an RCA 1802 microprocessor-based controller, which serves to collect and format data, to present data to a scan converter, and to operate a device communication bus. A NOVA minicomputer is used to record and recall frame images and to perform refined image processing. The RCA 1802 also provides instrument mode control for the MASCOT. Commands are issued using STOIC, a FORTH-like language. Sufficient flexibility has been provided so that a variety of CCDs can be accomodated. At present, Texas Instruments virtual phase CCDs are utilized. This is the second of two papers describing the MASCOT. © 1980 SPIE. All rights reserved.

关键词： Charge coupled devices

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Comparative Benchmarking Analysis of Next-Generation Space Processors

Comparative Benchmarking Analysis of Next-Generation Space P...

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IEEE Aerospace Conference

作者： Gretok, Evan W. Kain, Evan T. George, Alan D. Univ Pittsburgh Dept Elect & Comp Engn NSF Ctr Space High Performance & Resilient Comp S 4420 Bayard StSuite 560 Pittsburgh PA 15213 USA

ISBN: (纸本)9781538668542

Researchers, corporations, and government entities are seeking to deploy increasingly compute-intensive workloads on space platforms. This need is driving the development of two new radiation-hardened, multi-core space processors, the BAE systems RAD5545TM processor and the Boeing High-Performance Spaceflight Computing (HPSC) processor. As these systems remained in the development phase, the Freescale P5020DS and P5040DS systems, based on the same PowerPC e5500 architecture as the RAD5545 processor, and the Hardkernel ODROID-C2, sharing the same ARM Cortex-A53 core as the HPSC processor, were selected as facsimiles for evaluation. Several OpenMP-parallelized applications, including a color search, Sobel filter, Mandelbrot set generator, hyperspectral imaging target classifier, and image thumbnailer, were benchmarked on these processing platforms. Performance and energy consumption results on these facsimiles were scaled to forecasted frequencies of the radiation-hardened devices in development. In these studies, the RAD5545 achieved the highest and most consistent parallel efficiency, up to 99%. The HPSC processor achieved faster execution times, averaging about half that of the RAD5545 processor, with lower energy consumption. The evaluated applications reached up to 3.9 speedup across four cores. The frequency-scaling methods were validated by comparing the set of scaled measures with data points from an underclocked facsimile, which yielded an average accuracy of 97% between estimated and measured results. These performance outcomes help to establish the capabilities of both the RAD5545 and HPSC processors for on-board parallel processing of computationally-demanding applications for future space missions.

关键词： Program processors Performance evaluation Computer architecture Bandwidth parallel processing Space vehicles Benchmark testing

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