量子进化算法中种群大小的平方函数及其在分形图像压缩中的应用

2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications Pub Date : 2011-09-27 DOI:10.1109/BIC-TA.2011.1

Amin Qorbani, A. Nodehi, A. Ahmadi, S. Nodehi

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引用次数: 2

摘要

分形图像压缩是NP-Hard问题中一个众所周知的问题。量子进化算法是一种采用概率表示解的新型优化算法，非常适合于求解像背包问题这样的组合问题。遗传算法在分形图像压缩问题中得到了广泛的应用，而QEA算法在这类问题中还没有得到应用。本文改进了QEA算法，并将其应用于分形图像压缩中。实验结果表明，该方法比遗传算法和传统的分形图像压缩算法具有更好的性能。

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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 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.

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2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications

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