<b>Distributed systems applied to image compression and recovery</b> - DOI: 10.4025/actascitechnol.v30i1.3178
DOI:
https://doi.org/10.4025/actascitechnol.v30i1.3178Keywords:
MPI, digital image processing, distributed systemsAbstract
Digital image processing is a field that demands great processing capacity. As such, it becomes relevant to implement software that is based on the distribution of the processing into several nodes divided by computers belonging to the same network. Specifically discussed in this work are distributed algorithms of compression and expansion of images using the discrete cosine transform. The results show that the savings in processing time obtained due to the parallel algorithms, in comparison to its sequential equivalents, is a function that depends on the resolution of the image and the complexity of the involved calculation; that is, efficiency is greater the longer the processing period is in terms of the time involved for the communication between the network points.Downloads
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Published
2008-05-08
How to Cite
Gostaldon, F. J. A., & Shinoda, A. A. (2008). <b>Distributed systems applied to image compression and recovery</b> - DOI: 10.4025/actascitechnol.v30i1.3178. Acta Scientiarum. Technology, 30(1), 1–7. https://doi.org/10.4025/actascitechnol.v30i1.3178
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Section
Computer Science
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