A Novel Functional Sized Population Quantum Evolutionary Algorithm for Fractal Image Compression
Publish place: 14th annual International CSI Computer Conference
Publish Year: 1388
Type: Conference paper
Language: English
View: 2,265
This Paper With 6 Page And PDF Format Ready To Download
- Certificate
- I'm the author of the paper
این Paper در بخشهای موضوعی زیر دسته بندی شده است:
Export:
Document National Code:
CSICC14_063
Index date: 14 June 2009
A Novel Functional Sized Population Quantum Evolutionary Algorithm for Fractal Image Compression abstract
Quantum Evolutionary Algorithm (QEA) is a novel optimization algorithm which uses a probabilistic representation for solution and is highly suitable for combinatorial problems like Knapsack problem. Fractal image compression is a well-known problem which is in the class of NP-Hard problems. Genetic algorithms are widely used for fractal image compression problems, but QEA is not used for this kind of problems yet. This paper uses a novel Functional Sized population Quantum Evolutionary Algorithm for fractal image compression. Experimental results show that the proposed algorithm has a better performance than GA and conventional fractal image compression algorithms.
A Novel Functional Sized Population Quantum Evolutionary Algorithm for Fractal Image Compression Keywords:
A Novel Functional Sized Population Quantum Evolutionary Algorithm for Fractal Image Compression authors
Ali Nodehi
Islamic Azad University, Gorgan, Iran
Mohamad Tayarani
Islamic Azad University, Mashhad, Iran
Fariborz Mahmoudi
Islamic Azad University, Qazvin, Iran