Scalable parallel wavelet transforms for image processing

被引：1
作者：
Chadha, N [1 ]
Cuhadar, A [1 ]
Card, H [1 ]
机构：
[1] Univ Manitoba, Dept Elect & Comp Engn, Winnipeg, MB R3T 5V6, Canada
来源：
IEEE CCEC 2002: CANADIAN CONFERENCE ON ELECTRCIAL AND COMPUTER ENGINEERING, VOLS 1-3, CONFERENCE PROCEEDINGS | 2002年
关键词：
wavelet transform; distributed computing; image processing;
D O I：
10.1109/CCECE.2002.1013053
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, algorithms for 2D wavelet transform decomposition on clusters of workstations are described and analyzed. For the parallel algorithm employed in this Work, the computation of the transform is structured so that the exchange of intermediate transform coefficients is restricted only to neighboring processors and the amount of data communicated is independent of the problem size. Results show that the performance of the parallel implementation improves with increasing data size making the parallel algorithm particularly suitable for applications such as image processing, image coding and computer vision. Timings measured on a Myrinet connected Beowulf cluster agree well with the theoretical analysis and indicate that the implementation is cost Optimal.
引用
收藏
页码：851 / 856
页数：2
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