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检索条件"任意字段=Parallel and Distributed Methods for Image Processing II"

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parallel Implementation of Edge-Directed image Interpolation on a Graphics processing Unit

Parallel Implementation of Edge-Directed Image Interpolation...

引用

International Conference on parallel and distributed Systems (ICPADS)

作者： Jiaji Wu Tao Li Bormin Huang School of Electronic Engineering Xidian University Xi'an China Space Science and Engineering Center University of Wisconsin-Madison Madison USA

The edge-directed interpolation scheme is a non-iterative, orientation-adaptive method to enhance image resolution with better visual effect than conventional interpolation methods. It interpolates the missing pixels based on the covariance of a high-resolution image estimated from the covariance of the low-resolution image. In spite of the impressive performance, the computational complexity of covariance-based adaptation is significantly higher than that of the conventional linear interpolation algorithms. In this paper, we propose a GPU-based massively parallel version of the edge-directed interpolation scheme. A speedup of 61.7x can be achieved with respect to its single-threaded CPU counterpart in the host computer.

关键词： Interpolation Graphics processing unit Instruction sets image edge detection Streaming media Kernel Registers

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PATUS: A Code Generation and Autotuning Framework for parallel Iterative Stencil Computations on Modern Microarchitectures

PATUS: A Code Generation and Autotuning Framework for Parall...

引用

International Symposium on parallel and distributed processing (IPDPS)

作者： Matthias Christen Olaf Schenk Helmar Burkhart Department of Mathematics and Computer Science University of Basel Switzerland

Stencil calculations comprise an important class of kernels in many scientific computing applications ranging from simple PDE solvers to constituent kernels in multigrid methods as well as image processing applications. In such types of solvers, stencil kernels are often the dominant part of the computation, and an efficient parallel implementation of the kernel is therefore crucial in order to reduce the time to solution. However, in the current complex hardware micro architectures, meticulous architecture-specific tuning is required to elicit the machine's full compute power. We present a code generation and auto-tuning framework \textsc{Patus} for stencil computations targeted at multi- and many core processors, such as multicore CPUs and graphics processing units, which makes it possible to generate compute kernels from a specification of the stencil operation and a parallelization and optimization strategy, and leverages the auto tuning methodology to optimize strategy-dependent parameters for the given hardware architecture.

关键词： Hardware Kernel Instruction sets parallel processing Arrays Three dimensional displays

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parallel Automatic Registration of Large Scale Microscopic images on Multiprocessor CPUs and GPUs

Parallel Automatic Registration of Large Scale Microscopic I...

引用

IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Lee Cooper Kun Huang Manuel Ujaldon Center of Comprehensive Informatics Emory University Atlanta GA USA Biomedical Informatics Department Ohio State Uinversity Columbus OH USA Computer Architecture Department University of Malaga Malaga Spain

During the present decade, emerging architectures like multicore CPUs and graphics processing units (GPUs) have steadily gained popularity for their ability to deploy high computational power at a low cost. In this paper, we combine parallelization techniques on a cooperative cluster of multicore CPUs and multisocket GPUs to apply their joint computational power to an automatic image registration algorithm intended for the analysis of high-resolution microscope images. Registration methods pose a computational challenge within the biomedical field due to the large size of microscope image data sets, which typically extend to the Terabyte scale. We analyze this application to identify those parts which are more favorable to the CPU and GPU execution models and decompose the process accordingly. Performance results are presented for two sets of images: mouse placenta (16K × 16K pixels) and mouse mammary tumor (23K × 62K pixels). Execution times are shown on different multi-node, multi-socket and multi-core configurations to provide performance insights about the most effective approach.

关键词： Graphics processing unit Microscopy Multicore processing Sockets Random access memory parallel processing Hardware

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DEVELOPMENT OF methods FOR THE processing OF MEDICAL imageS USING GENETIC ALGORITHMS

DEVELOPMENT OF METHODS FOR THE PROCESSING OF MEDICAL IMAGES ...

引用

11th International Multidisciplinary Scientific GeoConference

作者： Licev, Lacezar Fabian, Tomas Tech Univ Ostrava FEECS Dept Comp Sci Ostrava Czech Republic

In this paper we deal with analysis and evaluation of objects of interest which are present in ultrasound images as well as assessment of the progress or regressions that occurred in these objects. These objects are highly significant from a medicinal perspective and include atherosclerostic plaque in carotid arteries, the intima-media thickness in the distal part of the common carotid artery, cerebral cortex size and brain stem Findings in cases of Parkinson disease. Here, we describe procedures employing combination of common methods and evolutionary algorithms for recognizing points of interest in the images that may serve in determining various parameters and properties of analyzed objects. We use the evolutionary algorithms to optimize the energy function of deformable models used to approximate the locations and shapes of object boundaries in images. We suppose that evolutionary algorithms can be used to find the desired global solution. Evolutionary algorithms are based on principles of evolution found in nature and respect the Darwin's theory of natural selection according to the defined cost function and gene recombination and mutation. As the computation of gradient vector flow field and also the evolution of active contour are computationally very expensive, we investigate the suitability of the GPU for a parallel implementation. In conclusion, we compare our approach with common numerical methods on real medical images segmentation.

关键词： medical imaging image segmentation active contour GVF snake SOMA

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Ball Detection with the Aim of Corner Event Detection in Soccer Video

Ball Detection with the Aim of Corner Event Detection in Soc...

引用

IEEE International Symposium on parallel and distributed processing with Applications Workshops (ISPAW)

作者： J. Hossein-Khani H. Soltanian-Zadeh M. Kamarei O. Staadt CIPCE Department of Electrical and Computer Engineering University of Tehran Tehran Iran Faculty of Computer Science University of Rostock Rostock Germany

In the present work, automatic corner detection in soccer games based on image features (e.g., object-based features) has been studied. For this purpose, a framework has been proposed that consists of five steps. This paper mainly focuses on the first three steps and specially ball detection step. Ball position on the field plays an important role in determining which event has occurred in the game. Therefore, it is necessary to detect exact position of the ball in the playfield and then track it. Ball trajectory that can be obtained via tracking is useful for identifying and detecting main events of soccer games. In these three steps, the most important processing that has been applied to the images is based on image segmentation to detect playfield, field lines, and ball. Cleaning morphological method is applied to detect the ball. This method is real-time and automatic, it yields superior results in comparison with other common methods such as Template Matching and Circular Hough Transform (CHT). By applying the proposed method, only one candidate for the ball position is obtained and non-ball candidates are removed, hence, it is more reliable than other methods. The results of the proposed method are compared with those of CHT. They illustrate that the proposed method is fast, effective, and reliable.

关键词： image color analysis Streaming media Feature extraction Shape Games Tracking Pixel

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Toolbox for advanced X-ray image processing

Toolbox for advanced X-ray image processing

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Conference on Advances in Computational methods for X-Ray Optics ii

作者： Gureyev, Timur E. Nesterets, Yakov Ternovski, Dimitri Thompson, Darren Wilkins, Stephen W. Stevenson, Andrew W. Sakellariou, Arthur Taylor, John A. CSIRO Mat Sci & Engn PB 33 Clayton Vic 3169 Australia Trident Software Pty Ltd Melbourne Vic 8006 Australia

ISBN: (纸本)9780819487513

A software system has been developed for high-performance Computed Tomography (CT) reconstruction, simulation and other X-ray image processing tasks utilizing remote computer clusters optionally equipped with multiple Graphics processing Units (GPUs). The system has a streamlined Graphical User Interface for interaction with the cluster. Apart from extensive functionality related to X-ray CT in plane-wave and cone-beam forms, the software includes multiple functions for X-ray phase retrieval and simulation of phase-contrast imaging (propagation-based, analyzer crystal based and Talbot interferometry). Other features include several methods for image deconvolution, simulation of various phase-contrast microscopy modes (Zernike, Schlieren, Nomarski, dark-field, interferometry, etc.) and a large number of conventional image processing operations (such as FFT, algebraic and geometrical transformations, pixel value manipulations, simulated image noise, various filters, etc.). The architectural design of the system is described, as well as the two-level parallelization of the most computationally-intensive modules utilizing both the multiple CPU cores and multiple GPUs available in a local PC or a remote computer cluster. Finally, some results about the current system performance are presented. This system can potentially serve as a basis for a flexible toolbox for X-ray image analysis and simulation, that can efficiently utilize modern multi-processor hardware for advanced scientific computations.

关键词： X-ray imaging Computed Tomography parallel programs Graphical processing Units computer clusters

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Fast double-parallel image processing based on FPGA

Fast double-parallel image processing based on FPGA

引用

IEEE International Conference on Vehicular Electronics and Safety (ICVES)

作者： Ye Li Qingming Yao Bin Tian Wencong Xu State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy and Sciences Beijing China School of Mechanical Electrical and Information Engineering Shandong University Weihai China

Due to FPGA's flexibility and parallelism, it is popular for accelerating image processing. In this paper, a double-parallel architecture based on FPGA has been exploited to speed up median filter and edge detection tasks, which are essential steps during image processing. The double-parallel scheme includes an image-level parallel and an operation-level parallel. The image-level parallel is a high-level parallel which divides one image into different parts and processes them concurrently. The operation-level parallel, which is embedded in each image-level parallel thread, fully explores every parallel part inside the concrete algorithms. The corresponding design is based on a DE2 Development Board which contains a CYCLONE ii FPGA device. Meanwhile, the same task has also been implemented on PC and DSP for performance comparison. Despite the fact that operating frequencies of used PC and DSP are much higher than FPGA's, FPGA costs less time per computed image than both of them. By taking advantage of the double-parallel technique, the speed/frequency ratio of FPGA is 202 times faster than PC and 147 times faster than DSP. Finally, a detailed discussion about different platforms is conducted, which analyzes advantages and disadvantages of used computing platforms. This paper reveals that the proposed double-parallel scheme can dramatically speed up image processing methods even on a low-cost FPGA platform with low frequency and limited resources, which is very meaningful for practical applications.

关键词： image edge detection Field programmable gate arrays Digital signal processing Hardware Kernel Detectors

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Solving k-Set Agreement with Stable Skeleton Graphs

Solving k-Set Agreement with Stable Skeleton Graphs

引用

IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Martin Biely Peter Robinson Ulrich Schmid EPF Lausanne Switzerland ECS Group Technische Universität Wien Austria Division of Mathematical Sciences Nanyang Technological University Singapore

In this paper we consider the k-set agreement problem in distributed message-passing systems using a round-based approach: Both synchrony of communication and failures are captured just by means of the messages that arrive within a round, resulting in round-by-round communication graphs that can be characterized by simple communication predicates. We introduce the weak communication predicate Psrcs(k) and show that it is tight for k-set agreement, in the following sense: We (i) prove that there is no algorithm for solving (k-1)-set agreement in systems characterized by Psrcs(k), and (ii) present a novel distributed algorithm that achieves k-set agreement in runs where Psrcs(k) holds. Our algorithm uses local approximations of the stable skeleton graph, which reflects the underlying perpetual synchrony of a run. We prove that this approximation is correct in all runs, regardless of the communication predicate, and show that graph-theoretic properties of the stable skeleton graph can be used to solve k-set agreement if Psrcs(k) holds.

关键词： Skeleton Approximation methods Approximation algorithms Computer crashes Computational modeling Erbium Proposals

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Tracking Structure of Streaming Social Networks

Tracking Structure of Streaming Social Networks

引用

IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： David Ediger Jason Riedy David A. Bader Henning Meyerhenke College of Computing Georgia Institute of Technology Atlanta GA USA

Current online social networks are massive and still growing. For example, Face book has over 500 million active users sharing over 30 billion items per month. The scale within these data streams has outstripped traditional graph analysis methods. Real-time monitoring for anomalies may require dynamic analysis rather than repeated static analysis. The massive state behind multiple persistent queries requires shared data structures and flexible representations. We present a framework based on the STINGER data structure that can monitor a global property, connected components, on a graph of 16 million vertices at rates of up to 240,000 updates per second on 32 processors of a Cray XMT. For very large scale-free graphs, our implementation uses novel batching techniques that exploit the scale-free nature of the data and run over three times faster than prior methods. Our framework handles, for the first time, real-world data rates, opening the door to higher-level analytics such as community and anomaly detection.

关键词： Arrays Program processors Facebook image color analysis Hardware

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Phase Map Generation for Phase Shift Moire Using CUDA

Phase Map Generation for Phase Shift Moire Using CUDA

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IEEE International Conference on parallel and distributed Computing, Applications and Technologies (PDCAT)

作者： Sudhakar Sah YoungJun Roh KyoungSeop Chang DaeHwa Jeong Center of Research in Engr Sciences and Tech-CREST KPIT Cummins Infosystems Limited Pune India FPG Productivity Research Institute LG Electronics Inc. South Korea

Phase shift Moiré is a very popular and one of the most successful techniques for shape measurement of 3-D objects such as PCB (printed circuit board), TFT (thin film transistor), LCD (Liquid crystal display) etc. Various implementations of phase shift moiré are available for improving accuracy and/or speed. Although, these methods contribute a lot in reducing the computation with some compromise in accuracy, there is a lot of scope of improving the performance of these algorithms with increased accuracy, especially when specialized hardware like GPU is available. GPU contains many core or processing elements that can process the same work concurrently resulting in dramatic increase in performance. In this paper, we propose the parallel implementation of the phase shift moiré method on CUDA. A novel method called image stacking method is proposed that can also be used for CUDA implementation of similar algorithms to improve performance. Using this technique, we are able to execute the application 180 times faster compared to the CPU implementation.

关键词： Graphics processing unit Instruction sets Kernel Three dimensional displays Computer architecture Pipeline processing Stacking

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