[1]陈聪梅,都政,井革新,等. 超级计算机的图像结构相似度并行处理方法[J].计算机技术与发展,2017,27(09):22-25.
　CHEN Cong-mei,DU Zheng,JING Ge-xin,et al. Research on Image SSIM Paralleling Algorithm with Super Computer[J].,2017,27(09):22-25.
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 超级计算机的图像结构相似度并行处理方法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年09期
页码:
22-25
栏目:
智能、算法、系统工程
出版日期:
2017-09-10

文章信息/Info

Title:
 Research on Image SSIM Paralleling Algorithm with Super Computer
文章编号:
1673-629X（2017)09-0022-04
作者:
 陈聪梅; 都政; 井革新; 赵晓惠; 靳绍巍; 陈远磊; 饶青雷; 邬鸿
 国家超级计算深圳中心(深圳云计算中心)
Author(s):
 CHEN Cong-mei; DU Zheng; JING Ge-xin; ZHAO Xiao-hui ; JIN Shao-wei; CHEN Yuan-lei; RAO Qing-lei ；WU Hong
关键词:
 ; 数字图像; 超级计算机; 结构相似度; 加速比
Keywords:
 ; digital image; supercomputing; SSIM; accelerating ratio
分类号:
TP312
文献标志码:
A
摘要:
 随着图像信息量呈指数级的增长,图像处理面临效率低与质量差的双重挑战,图像结构相似度作为图像质量评价领域常用的一种方法也面临着同样的问题.为此,提出了一种基于超级计算机的数字图像结构相似度并行处理方法.基于超算中心的高性能计算平台实现图像结构相似度的并行处理,采用分块并行计算图像的三种信息,通过与单机计算比较来评价并行处理的性能.实验结果表明,针对数据量大的图像,采用所提出的并行处理方案的耗时远低于单机计算所耗费的时间,可获得较大的加速比,并有效地提高计算效率.可见,所提出的基于超级计算机的图像结构相似度并行处理方法有效可行,为实现图像实时处理提供了可能性.
Abstract:
 With the exponential growth of image information,image processing is faced with the dual challenge of low inefficiencies and poor quality. Image Structural Similarity ( SSIM) ,taken as a common method in the field of image quality assessment,is also faced with the identical problem. Therefore,a method of image SSIM parallel processing based on supercomputers is proposed. The image SSIM par-allel processing is implemented based on High Performance Supercomputer Center with computing resources. The three kinds of image in-formation are in the parallel calculation by blocking. The performance of the parallel processing is simulated compared with the serial cal-culation. The experimental results indicate that in allusion to massive image data,it is far lower in the operation time than serial calculation with larger accelerating ratio and higher efficiency,which is effective and feasible,and makes the real-time processing of image possible.

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更新日期/Last Update: 2017-10-19