Single Instruction Multiple Data (SIMD) approach for Efficient Fractal Image Encoding using Distributed Architecture

Akhilesh Kumar*, G. R. Sinha**, Vikas Dilliwar***
* PG Student, Department of Computer Science & Engineering, Shri Shankarachrya Technical Campus Bhilai, India.
** Professor and Associate Director, Shri Shankarachrya Technical Campus Bhilai, India.
*** Research Scholar, Department of Computer Science & Engineering, Chhattisgarh Institute of Technology, Rajnandgaon, India.
Periodicity:December - February'2015
DOI : https://doi.org/10.26634/jpr.1.4.3308

Abstract

There are several application areas where tremendous computational resources are required including image processing, big data and genetic mapping which are computationally intensive areas. Huge computing resources are required to solve such complex problems and powerful computing environment is needed. An emphasis is made on fractal image compression, which requires higher computing needs to solve. Single Instruction Multiple Data approach is followed using distributed architecture. The research compares the performance on the basis of speed up and encoding time. It was found that image compression requires more computing power to solve in lesser time. In this paper, the parallel algorithms are developed using Distributed Fractal Image Encoding Architecture (DFIE) as Single Instruction Multiple Data (SIMD) approach

Keywords

Distributed Fractal Image Compression, Computing Nodes, Encoding and Contractive Mapping.

How to Cite this Article?

Kumar, A., Sinha, G. R., and Dilliwar, V. (2015). Single Instruction Multiple Data (SIMD) approach for Efficient Fractal Image Encoding using Distributed Architecture. i-manager’s Journal on Pattern Recognition, 1(4), 28-34. https://doi.org/10.26634/jpr.1.4.3308

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