Complete image partitioning on spiral architecture

Qiang Wu, Xiangjian He, Tom Hintz, Yuhuang Ye

Research output: Chapter in Book/Conference proceedingBook Chapterpeer-review

4 Citations (Scopus)

Abstract

Uniform image partitioning has been achieved on Spiral Architecture, which plays an important role in parallel image processing on many aspects such as uniform data partitioning, load balancing, zero data exchange between the processing nodes et al. However, when the number of partitions is not the power of seven like 49, each sub-image except one is split into a few fragments which are mixed together. We could not tell which fragments belong to which sub-image. It is an unacceptable flaw to parallel image processing. This paper proposes a method to resolve the problem mentioned above. From the experimental results, it is shown that the proposed method correctly identifies the fragments belonging to the same sub-image and successfully collects them together to be a complete sub-image. Then, these sub-images can be distributed into the different processing nodes for further processing.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMinyi Guo, Laurence Tianruo Yang
PublisherSpringer Verlag
Pages304-315
Number of pages12
ISBN (Print)9783540376194
DOIs
Publication statusPublished - 2003
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2745
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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