Square Function for Population Size in Quantum Evolutionary Algorithm and its Application in Fractal Image Compression

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 for solutions and is highly suitable for combinatorial problems like Knapsack problem. Genetic algor...

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Bibliographic Details
Main Authors: Qorbani, A., Nodehi, A., Ahmadi, A., Nodehi, S.
Format: Conference Proceeding
Language:English
Subjects:
Bismuth
Evolutionary computation
Fractal Image Compression
Fractals
Genetic algorithms
Image coding
Measurement
Nickel
Optimization Method
Quantum Evolutionary Algorithms
Online Access:Request full text
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Summary: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 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 this kind of problems yet. This paper improves QEA whit change population size and used it in fractal image compression. Experimental results show that our method have a better performance than GA and conventional fractal image compression algorithms.
DOI:10.1109/BIC-TA.2011.1