Parallel fractal image compression
In this report, considerations such as PSNR, compression ratio, compression time versus number of processors and the workload granularity are also presented.
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2008
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Online Access: | http://hdl.handle.net/10356/2723 |
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sg-ntu-dr.10356-27232023-03-04T03:19:46Z Parallel fractal image compression Toh, Guan Nge. School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing In this report, considerations such as PSNR, compression ratio, compression time versus number of processors and the workload granularity are also presented. RG 49/95 2008-09-17T09:13:49Z 2008-09-17T09:13:49Z 2000 2000 Research Report http://hdl.handle.net/10356/2723 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Toh, Guan Nge. Parallel fractal image compression |
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In this report, considerations such as PSNR, compression ratio, compression time versus number of processors and the workload granularity are also presented. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Toh, Guan Nge. |
format |
Research Report |
author |
Toh, Guan Nge. |
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Toh, Guan Nge. |
title |
Parallel fractal image compression |
title_short |
Parallel fractal image compression |
title_full |
Parallel fractal image compression |
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Parallel fractal image compression |
title_full_unstemmed |
Parallel fractal image compression |
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parallel fractal image compression |
publishDate |
2008 |
url |
http://hdl.handle.net/10356/2723 |
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1759853522928533504 |