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4th International Congress on image and Signal processing, CISP 2011

作者： Li, Yuecheng Zhang, Hong You, Yuhu Sun, Mingui School of Astronautics Beihang University Beijing China Departments of Neurosurgery Electrical and Computer Engineering and Bioengineering University of Pittsburgh Pittsburgh United States

ISBN: (纸本)9781424493067

Retinex is one of the well-known schemes for adaptive image enhancement under poor weather conditions. Improving the visibility of input images on a target detection system is necessary to insure detection work properly. Compared to other realization methods based on DSPs and FPGAs, this paper proposes a totally parallel structure based on FPGA to implement multi-scale Retinex for an outdoor application. Gaussian kernel is optimized with address encoding and distributed arithmetic, and parallel multi-scale convolutions are realized. No frame buffer is needed for the proposed implementation itself, so the system delay is greatly saved. Experiments show the good performance of the proposed multi-scale Retinex implementation by both subjective and objective assessments. Visibility of images suffering from fog degradation and uneven light is improved. And future work is presented in the conclusion. © 2011 IEEE.

关键词： image enhancement

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parallel biomedical image processing with GPGPUs in cancer research

Parallel biomedical image processing with GPGPUs in cancer r...

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3rd IEEE International Symposium on Logistics and Industrial Informatics, LINDI 2011

作者： Reményi, Attila Szénási, Sándor Bándi, István Vámossy, Zoltán Valcz, Gábor Bogdanov, Pál Sergyán, Szabolcs Kozlovszky, Miklos Óbuda University John von Neumann Faculty of Informatics Budapest Hungary Semmelweiss University 2nd Department of Internal Medicine Budapest Hungary MTA SZTAKI/Laboratory of Parallel and Distributed Computing Budapest Hungary

ISBN: (纸本)9781457718410

The main aim of this work is to show, how GPGPUs can facilitate certain type of image processing methods. The software used in this paper is used to detect special tissue part, the nuclei on (HE - hematoxilin eosin) stained colon tissue sample images. Since pathologists are working with large number of high resolution images - thus require significant storage space -, one feasible way to achieve reasonable processing time is the usage of GPGPUs. The CUDA software development kit was used to develop processing algorithms to NVIDIA type GPUs. Our work focuses on how to achieve better performance with coalesced global memory access when working with three-channel RGB tissue images, and how to use the on-die shared memory efficiently. © 2011 IEEE.

关键词： image processing

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Rigorous Calculation of the Partition Function for the Finite Number of Ising Spins

Rigorous Calculation of the Partition Function for the Finit...

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4th International Multi-Conference on Engineering and Technological Innovation

作者： Peretyatko, Alexey A. Bogatyrev, Ivan A. Kirienko, Yury V. Nefedev, Konstantin V. Belokon, Valery I. Far Eastern Fed Univ Sch Nat Sci Sukhanova Str 8-43 Vladivostok Russia

ISBN: (纸本)9781936338375

The high-performance scalable parallel algorithm for rigorous calculation of partition function of lattice systems with finite number Ising spins was developed. The parallel calculations run by C++ code with using of Message Passing Interface and massive parallel instructions. The algorithm can be used for the research of the interacting spin systems in the Ising models of 2D and 3D. The processing power and scalability is analyzed for different parallel and distributed systems. Different methods of the speed up measuring allow obtain the super-linear speeding up for the small number of processes. Program code could be useful also for research by exact method of different Ising spin systems, e.g. system with competition interactions.

关键词： Massive-parallel Algorithm MPI C plus parallel and Disributed Calculations Ising Model Partition Function Statistical Mechanics

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A fast forward projection using multithreads for multirays on GPUs in medical image reconstruction

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MEDICAL PHYSICS 2011年第7期38卷 4052-4065页

作者： Chou, Cheng-Ying Chuo, Yi-Yen Hung, Yukai Wang, Weichung Natl Taiwan Univ Dept Bioind Mechatron Engn Taipei 106 Taiwan Natl Taiwan Univ Dept Math Taipei 106 Taiwan

Purpose: Iterative reconstruction techniques hold great potential to mitigate the effects of data noise and/or incompleteness, and hence can facilitate the patient dose reduction. However, they are not suitable for routine clinical practice due to their long reconstruction times. In this work, the authors accelerated the computations by fully taking advantage of the highly parallel computational power on single and multiple graphics processing units (GPUs). In particular, the forward projection algorithm, which is not included in the close-form formulas, will be accelerated and optimized by using GPU here. methods: The main contribution is a novel forward projection algorithm that uses multithreads to handle the computations associated with a bunch of adjacent rays simultaneously. The proposed algorithm is free of divergence and bank conflict on GPU, and benefits from data locality and data reuse. It achieves the efficiency particularly by (i) employing a tiled algorithm with three-level parallelization, (ii) optimizing thread block size, (iii) maximizing data reuse on constant memory and shared memory, and (iv) exploiting built-in texture memory interpolation capability to increase efficiency. In addition, to accelerate the iterative algorithms and the Feldkamp-Davis-Kress (FDK) algorithm on GPU, the authors apply batched fast Fourier transform (FFT) to expedite filtering process in FDK and utilize projection bundling parallelism during backprojection to shorten the execution times in FDK and the expectation-maximization (EM). Results: Numerical experiments conducted on an NVIDIA Tesla C1060 GPU demonstrated the superiority of the proposed algorithms in computational time saving. The forward projection, filtering, and backprojection times for generating a volume image of 512 x 512 x 512 with 360 projection data of 512 x 512 using one GPU are about 4.13, 0.65, and 2.47 s (including distance weighting), respectively. In particular, the proposed forward projection alg

关键词： x-ray CT medical image reconstruction forward projection iterative algorithms graphics processing unit (GPU) compute unified device architecture (CUDA)

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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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2011 12th International Conference on parallel and distributed Computing, Applications and Technologies, PDCAT 2011

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

ISBN: (纸本)9780769545646

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. © 2011 IEEE.

关键词： Graphics processing unit

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Color image edge detection based on quantity of color information and its implementation on the GPU

Color image edge detection based on quantity of color inform...

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IASTED International Conference on parallel and distributed Computing and Systems, PDCS 2011

作者： Zhao, Jingxiu Xiang, Yonghong Dawson, Laurence Wart, Iain St School of Computer Science Qufu Normal University Rizhao 276826 China School of Engineering and Computing Sciences Durham University Durham DH1 3LE United Kingdom

ISBN: (纸本)9780889869073

In this paper, we present a new method for quantifying color information so as to detect edges in color images. Our method uses the volume of a pixel in the HSI color space, allied with noise reduction, thresholding and edge thinning. We implement our algorithm using NVIDIA Compute Unified Device Architecture (CUDA) for direct execution on Graphics processing Units (GPUs). Our experimental results show that: compared to traditional edge detection methods, our method can improve the accuracy of edge detection and withstand greater levels of noise in images;and our GPU implementation achieves speedups over related CUDA implementations.

关键词： Graphics processing unit

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A parallel resampling scheme and its application to distributed particle filtering in wireless networks

A parallel resampling scheme and its application to distribu...

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2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive processing, CAMSAP 2011

作者： Achutegui, Katrin Miguez, Joaquin Department of Signal Theory and Communications Universidad Carlos III de Madrid Avenida de la Universidad 30 28911 Leganés Madrid Spain

ISBN: (纸本)9781457721052

We address the design of a particle filter (PF) that can be implemented in a distributed manner over a network of wireless sensor nodes, each of them collecting their own local data. This is a problem that has received considerable attention lately and several methods based on consensus, the transmission of likelihood information, the truncation and/or the quantization of data have been proposed. However, all existing schemes suffer from limitations related either to the amount of required communications among the nodes or the accuracy of the filter outputs. In this work we propose a novel distributed PF that is built around the distributed resampling with non-proportional allocation (DRNA) algorithm. This scheme guarantees the properness of the particle approximations produced by the filter and has been shown to be both efficient and accurate when compared with centralized PFs. The standard DRNA technique, however, places stringent demands on the communications among nodes that turn out impractical for a typical wireless sensor network (WSN). In this paper we investigate how to reduce this communication load by using (i) a random model for the spread of data over the WSN and (ii) methods that enable the out-of-sequence processing of sensor observations. A simple numerical illustration of the performance of the new algorithm compared with a centralized PF is provided. © 2011 IEEE.

关键词： Sensor nodes

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Performance Analysis of Mammographic image Enhancement Techniques for Early Detection of Breast Cancer

Performance Analysis of Mammographic Image Enhancement Techn...

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1st International Conference on Computer Science, Engineering and Information Technology (CCSEIT 2011)

作者： Singh, Shailaja Yadav, Anamika Singh, Bikesh Kumar MPCCET Dept Comp Sci & Engn Bhilai India NIT Dept Elect Engn Raipur Madhya Pradesh India

ISBN: (纸本)9783642240362;9783642240379

Mammogram breast cancer images have the ability to assist physician in detection of disease caused by cells normal growth. Developing algorithms and software to analyse these images may also assist physicians in their daily work. Micro calcifications are tiny calcium deposits in breast tissues. They appear as small bright spots on mammograms. Since micro calcifications are small and subtle abnormalities, they may he overlooked by an examining radiologist. image Enhancement and Filtering is always the root process in many medical image processing applications. It is aimed at reducing noise in images. In this paper we have made comparison between several novel and hybrid enhancement techniques. The comparison is based on the basis of performance evaluation parameters (statistical parameter) such as PSNR, and CNR. These can be used for identifying breast nodule malignancy to provide better chance of a proper treatment. These methods are tested on digital mammograms present in mini-MIAS database.

关键词： Mammograms image Enhancement Spatial Filtering Contrast to noise ratio (CNR) Signal to noise ratio (PSNR)

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基于FPGA超声信号数字动态滤波器的实现

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现代生物医学进展 2012年第2期12卷 344-347页

作者：朱利华武剑辉栾强厚电子科技大学生命科学与技术学院四川成都610054 东莞电子科技大学电子信息工程研究院广东东莞523808

目的:本文研究了基于现场可编程门阵列(Field Programmable Gate Array,FPGA)超声成像系统中数字动态滤波器的实现方法和过程。方法:动态滤波器中FIR滤波器采用分布式算法(distributed Arithmetic,DA)实现结构,并在应用中对DA算法进行... 详细信息

目的:本文研究了基于现场可编程门阵列(Field Programmable Gate Array,FPGA)超声成像系统中数字动态滤波器的实现方法和过程。方法:动态滤波器中FIR滤波器采用分布式算法(distributed Arithmetic,DA)实现结构,并在应用中对DA算法进行了改进,包括数据并行处理结构的设计、对查找表(Look Up Table,LUT)输入字长N大小的控制和具有对称系数的FIR滤波器的采用。改进后的DA实现在FPGA资源占用和处理速度之间达到了平衡。同时,结合多级流水线结构,动态滤波器实现了数字超声信号并行处理。结果:采用常值滤波器(远场匹配参数)进行滤波后,超声回波图像远场分辨率达到了要求,但越靠近近场效果越差。相比之下,本文设计的基于FPGA超声信号动态数字滤波器达到了很好的滤波效果,使回声图像近场和远场都有最佳分辨率。结论:利用FPGA实现超声系统中动态滤波器是完全可行的,并且有助于提高系统的稳定性和可靠性,并大大减低系统成本。

关键词：超声信号动态滤波分布式算法 FIR滤波器 FPGA

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Biomedical image processing with GPGPU using CUDA

Biomedical image processing with GPGPU using CUDA

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作者： Firstauthor, A.R. Secondauthor, I.B. Thirdauthor, G.V. Fourthauthor, P.B. Fifthauthor, M.K. Buda University John von Neumann Faculty of Informatics Budapest Hungary Semmelweiss University 2nd Department of Internal Medicine Budapest Hungary MTA SZTAKI Laboratory of Parallel and Distributed Computing Budapest Hungary

ISBN: (纸本)9789532330670

The main aim of this work is to show, how the GPGPUs can be used to speed up certain image processing methods. The algorithm explained in this paper is used to detect nuclei on (HE hematoxilin eosin) stained colon tissue sample images, and includes a Gauss blurring, an RGB-HSV color space conversion, a fixed binarization, an ultimate erode procedure and a local maximum search. Since the images retrieved from the digital slides require significant storage space (up to few hundred megapixels), the usage of GPGPUs to speed up image processing operations is necessary in the interest of achieving reasonable processing time. The CUDA software development kit was used to develop algorithms to GPUs made by NVIDIA. This work focuses on how to achieve coalesced global memory access when working with three-channel RGB images, and how to use the on-die shared memory efficiently. The exact test algorithm also included a linear connected component labeling, which was running on the CPU, and with iterative optimization of the GPU code, we managed to achieve significant speed up in well defined test environment. © 2011 MIPRO.

关键词： Iterative methods

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