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Using Triangular Function To Improve Size Of Population In Quantum Evolution Algorithm For Fractal Image Compression

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Author(s): Amin Qorbani | Ali Nodehi | Saeed Nodehi

Journal: Advanced Computing : an International Journal
ISSN 2229-726X

Volume: 2;
Issue: 6;
Start page: 137;
Date: 2011;
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Keywords: Optimization Method | Quantum Evolutionary Algorithms | Genetic Algorithms | Fractal Image Compression

ABSTRACT
Fractal Image Compression is a well-known problem which is in the class of NP-Hard problems.Quantum Evolutionary Algorithm is a novel optimization algorithm which uses a probabilisticrepresentation for solutions and is highly suitable for combinatorial problems like Knapsack problem.Genetic algorithms are widely used for fractal image compression problems, but QEA is not used for thiskind of problems yet. This paper improves QEA whit change population size and used it in fractal imagecompression. Utilizing the self-similarity property of a natural image, the partitioned iterated functionsystem (PIFS) will be found to encode an image through Quantum Evolutionary Algorithm (QEA) methodExperimental results show that our method has a better performance than GA and conventional fractalimage compression algorithms.
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