Nowadays, single-chip cache-coherent multi-cores up to 100 cores are a reality and many-cores of hundreds of cores are planned in the near future. This technological shift undertaking by the high-end computer-industry...
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Nowadays, geographical computation presents to be distributed, parallel, and diversification application trend. Influence of problem scale and response speed requirement received more attention. And high performance c...
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ISBN:
(纸本)9783037854471
Nowadays, geographical computation presents to be distributed, parallel, and diversification application trend. Influence of problem scale and response speed requirement received more attention. And high performance computational systems, such as "TianHe 1-A", provides a new generation of hardware supports. In order to make full use of these high performance computational resources, appropriate and efficient parallel algorithms are needed. New parallel computing optimization technique of the geography is proposed in this paper by designing new parallel algorithms for slope analysis. We implement it based on CUDA. Experimental results with random DEM data in uniform distribution validate our methods.
Fluoroscopic images exhibit severe signal-dependent quantum noise, due to the reduced X-ray dose involved in image formation, that is generally modelled as Poisson-distributed. However, image gray-level transformation...
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Fluoroscopic images exhibit severe signal-dependent quantum noise, due to the reduced X-ray dose involved in image formation, that is generally modelled as Poisson-distributed. However, image gray-level transformations, commonly applied by fluoroscopic device to enhance contrast, modify the noise statistics and the relationship between image noise variance and expected pixel intensity. image denoising is essential to improve quality of fluoroscopic images and their clinical information content. Simple average filters are commonly employed in real-time processing, but they tend to blur edges and details. An extensive comparison of advanced denoising algorithms specifically designed for both signal-dependent noise (AAS, BM3Dc, HHM, TLS) and independent additive noise (AV, BM3D, K-SVD) was presented. Simulated test images degraded by various levels of Poisson quantum noise and real clinical fluoroscopic images were considered. Typical gray-level transformations (e.g. white compression) were also applied in order to evaluate their effect on the denoising algorithms. Performances of the algorithms were evaluated in terms of peak-signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), mean square error (MSE), structural similarity index (SSIM) and computational time. On average, the filters designed for signal-dependent noise provided better image restorations than those assuming additive white Gaussian noise (AWGN). Collaborative denoising strategy was found to be the most effective in denoising of both simulated and real data, also in the presence of image gray-level transformations. White compression, by inherently reducing the greater noise variance of brighter pixels, appeared to support denoising algorithms in performing more effectively. (C) 2012 Elsevier Ltd. All rights reserved.
This paper presents a design for parallelprocessing of synthetic aperture radar (SAR) data using multiple Graphics processing Units (GPUs). Our approach supports real-time reconstruction of a two-dimensional image fr...
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ISBN:
(纸本)9781467356046
This paper presents a design for parallelprocessing of synthetic aperture radar (SAR) data using multiple Graphics processing Units (GPUs). Our approach supports real-time reconstruction of a two-dimensional image from a matrix of echo pulses and their response values. Key to runtime efficiency is a partitioning scheme that divides the output image into tiles and the input matrix into a collection of pulses associated with each tile. Each image tile and its associated pulse set are distributed to thread blocks across multiple GPUs, which support parallel computation with near-optimal I/O cost. The partial results are subsequently combined by a host CPU. Further efficiency is realized by the GPU's low-latency thread scheduling, which masks memory access latencies. Performance analysis quantifies runtime as a function of input/output parameters and number of GPUs. Experimental results were generated with 10 nVidia Tesla C2050 GPUs having maximum throughput of 972 Gflop/s. Our approach scales well for output (reconstructed) image sizes from 2,048 x 2,048 pixels to 8,192 x 8,192 pixels.
In scanning x-ray microscopy, Differential Phase Contrast (DPC) imaging is a technique to image the phase contrast information. It is based on the concept that locally a sample can be considered as a prism, which defl...
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In scanning x-ray microscopy, Differential Phase Contrast (DPC) imaging is a technique to image the phase contrast information. It is based on the concept that locally a sample can be considered as a prism, which deflects the incident x-ray beam slightly in angle. Many efforts have been made in DPC imaging and a number of representative cases at a moderate spatial resolution have demonstrated the success of the method. However, the inherent limitations of those methods prevent DPC imaging from ultra-high spatial resolution imaging applications. A highly robust approach to DPC imaging based on Fourier-shift fitting was proposed recently. This method is effective in reconstructing the buried nanoscale interfacial structures. Because of the non-linear fitting and Fourier transformation operations involved in the algorithm, the computation is intensive at each scanning point. One challenge in this method is to make it fast enough to keep up with pixel-wise scanning, so that real-time data processing can be achieved. Here we provided three implementations in Matlab, Python and C++ and compared their speed performance. Experiments show that the C++ version is about one order of magnitude faster than the Matlab version and nearly two orders of magnitude faster than the Python version. In addition, we designed a parallel algorithm to divide the task into a number of independently running routines executing on a batch-queue based multi-core servers cluster and achieved almost another two orders of magnitude improvement.
Digital images and videos are used in many digital devices recently. Also, the resolution of display became larger than that of previous years. image up-scaling algorithm is important issue since original input source...
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ISBN:
(纸本)9780819489425
Digital images and videos are used in many digital devices recently. Also, the resolution of display became larger than that of previous years. image up-scaling algorithm is important issue since original input source is limited in transferring within data bandwidth. Among various up-scaling algorithms, Super-Resolution (SR) image reconstruction method is able to estimate high-resolution (HR) image using multiple low-resolution (LR) images. Conventional approaches to estimate HR image with Least Square (LS) method and Weighted Least Square (WLS) method are not able to reconstruct high-frequency region effectively in case its blur kernel is assumed Gaussian kernel in unknown system. Also, these methods produce jagging artifacts from the deficiency of LR frames. The proposed SR algorithm uses edge adaptive WLS method to reconstruct high-frequency region considering local properties and is applied to video sequence with block process to cope with local motions. Moreover, to apply video sequence with complex motions, we use selectively the correct information of reference frame to avoid errors from incorrect information. For accurate additional information from reference frames, the proposed algorithm determines additional information in reference frame by comparing with current frame and reference frame. The experiments demonstrate the superior performance of the proposed algorithm.
Network anomalies refer to situations when observed network traffic deviate from normal network behaviour. In this paper, we propose a general framework which assumes the use of many different attack detection methods...
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ISBN:
(纸本)9783642314995;9783642315008
Network anomalies refer to situations when observed network traffic deviate from normal network behaviour. In this paper, we propose a general framework which assumes the use of many different attack detection methods and show a way to integrate their results. We checked our approach by the use of network topology analysis methods applied to communication graphs. Based on this evaluation, we have proposed a measure called the Attack Score, which assesses the risk of an on-going attack and distinguishes between the effectiveness of the analytic measures used to detect it.
Magnetic resonance imaging (MRI) is currently widely used in medical image diagnosis. However, MR scanners are extensively used in clinics and thus are rarely accessible for experimentation. In consequence, the number...
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ISBN:
(纸本)9788372835024
Magnetic resonance imaging (MRI) is currently widely used in medical image diagnosis. However, MR scanners are extensively used in clinics and thus are rarely accessible for experimentation. In consequence, the number of images available for imageprocessingmethods evaluation is too low and there appears a need for a method to generate synthetic images. In their previous works, the authors studied various methods for blood vessels segmentation and tracking. Effectiveness of the designed algorithms requires objective verification which implies repetition of experiments for large number of images and comparing the results with some ground truth models. Therefore, this study aims at designing a computer system which implements numerical routines for generation of synthetic MRA images. In particular, in this paper we study the performance of various configurations of assembled computer grid and analyze their potential in angiographic image synthesis.
Color images formed by modern digital cameras are often noisy, especially if they are captured in bad illumination conditions. This makes desirable to remove the noise by image pre-filtering. A specific feature of the...
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ISBN:
(纸本)9780819489425
Color images formed by modern digital cameras are often noisy, especially if they are captured in bad illumination conditions. This makes desirable to remove the noise by image pre-filtering. A specific feature of the noise observed for the considered application is that it can be spatially correlated. Filters to be applied have to effectively suppress noise introducing only negligible distortions into processed images. Moreover, such filters have to be fast enough and tested for a variety of natural images and noise properties. Another specific requirement is that a visual quality of processed images has to be paid a specific attention. To carry out intensive testing of some denoising approaches, a recently designed database TID2008 of distorted images provides a good opportunity since it contains 25 different images corrupted by i.i.d. and spatially correlated noise with several levels of variances. Taking into account the known fact that the color components are highly correlated, both modern 2D (component-wise) and 3D (vector) filtering techniques are studied. It is demonstrated that the use of 3D filters that allow exploiting inter-channel correlation provides considerably better results in terms of conventional and visual quality metrics. It is also shown how 3D filter based on discrete cosine transform (DCT) can be adapted to a spatial correlation of noise. This adaptation produces sufficient increase of the filter's efficiency. Examples of filter's performance are presented.
In west DEMS areas of aerospace, MDO (Multidisciplinary Design Optimization) was the latest and most active design methods in recent years. Its main thinking is that: using DCNT (distributed Computer Network Technolog...
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ISBN:
(纸本)9783037854471
In west DEMS areas of aerospace, MDO (Multidisciplinary Design Optimization) was the latest and most active design methods in recent years. Its main thinking is that: using DCNT (distributed Computer Network Technology) to integrate knowledge of all subjects;using effective design optimization strategy to organize and manage of the design process. Its objective is to get the overall optimal solution by using the interaction and synergy between all subjections;to shorten the cycle by implementing of the parallel design. So that the developed the product would be more competitive. This thesis researched MDO development situation of home and aboard from three parts: Techniques and methods, Integrated Framework software and Application for getting some inspiration how to research MDO now.
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