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Matching search in fractal video compression and its parallel implementation in distributed computing environments

Matching search in fractal video compression and its parallel implementation in distributed computing environments

Wang, Meiqing, Huang, Zhehuang and Lai, Choi-Hong (2005) Matching search in fractal video compression and its parallel implementation in distributed computing environments. Applied Mathematical Modelling, 30 (8). pp. 677-687. ISSN 0307-904X (doi:10.1016/j.apm.2005.05.018)

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Abstract

Fractal video compression is a relatively new video compression method. Its attraction is due to the high compression ratio and the simple decompression algorithm. But its computational complexity is high and as a result parallel algorithms on high performance machines become one way out. In this study we partition the matching search, which occupies the majority of the work in a fractal video compression process, into small tasks and implement them in two distributed computing environments, one using DCOM and the other using .NET Remoting technology, based on a local area network consists of loosely coupled PCs. Experimental results show that the parallel algorithm is able to achieve a high speedup in these distributed environments.

Item Type: Article
Additional Information: [1] Paper published in special issue of Applied Mathematical Modelling titled: Parallel and distributed computing for computational mechanics.
Uncontrolled Keywords: fractal video compression, distributed computing, parallel algorithm, local area network, DCOM, .NET remoting
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Computational Science & Engineering Group
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
School of Computing & Mathematical Sciences > Statistics & Operational Research Group
Related URLs:
Last Modified: 14 Oct 2016 09:02
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/993

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