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SINUSOIDAL FUNCTION FOR POPULATION SIZE IN QUANTUM EVOLUTIONARY ALGORITHM AND ITS APPLICATION IN FRACTAL IMAGE COMPRESSION

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

Journal: Signal & Image Processing
ISSN 2229-3922

Volume: 2;
Issue: 2;
Start page: 10;
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 probabilistic representation forsolutions 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 this kind of problems yet.This paper improves QEA whit change population size and used it in fractal image compression. Utilizing the self-similarity property of a natural image, the partitioned iterated function system (PIFS) will be found to encode an image through Quantum Evolutionary Algorithm (QEA) method Experimental results show that our method has a better performance than GA and conventional fractal image compression algorithms.
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