Title :
Square Function for Population Size in Quantum Evolutionary Algorithm and its Application in Fractal Image Compression
Author :
Qorbani, Amin ; Nodehi, A. ; Ahmadi, Ali ; Nodehi, Saeed
Author_Institution :
Kordkoy Branch, Islamic Azad Univ., Kordkoy, Iran
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 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.
Keywords :
data compression; evolutionary computation; genetic algorithms; image coding; Knapsack problem; NP hard problems; combinatorial problems; fractal image compression; genetic algorithms; population size; probabilistic representation; quantum evolutionary algorithm; square function; Bismuth; Evolutionary computation; Fractals; Genetic algorithms; Image coding; Measurement; Nickel; Fractal Image Compression; Genetic Algorithms; Optimization Method; Quantum Evolutionary Algorithms;
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2011 Sixth International Conference on
Conference_Location :
Penang
Print_ISBN :
978-1-4577-1092-6
DOI :
10.1109/BIC-TA.2011.1
