Abstract
We apply a variant of Simulated Annealing (SA) as a standard black-box optimisation algorithm to the colour quantisation problem. The main advantage of black-box optimisation algorithms is that they do not require any domain specific knowledge yet are able to provide a near optimal solution. To further improve the performance of the algorithm we combine the SA technique with a standard k-means clustering technique. We evaluate the effectiveness of our approach by comparing its performance with several specialised colour quantisation algorithms. The results obtained show that our hybrid SA algorithm clearly outperforms standard quantisation algorithms and provides images with superior image quality.
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References
Y. Davidor. Epistasis variance: Suitability of a representation to genetic algorithms. Complex Systems, 4:369–383, 1990.
A.H. Dekker. Kohonen neural networks for optimal colour quantization. Network: Computation in Neural Systems, 5:351–367, 1994.
M. Gervautz and W. Purgathofer. A simple method for color quantization: Octree quantization. In A.S. Glassner, editor, Graphics Gems, pages 287–293. 1990.
P. S. Heckbert. Color image quantization for frame buffer display. ACM Computer Graphics (ACM SIGGRAPH’ 82 Proceedings), 16(3):297–307, 1982.
J.H. Holland. Adaptation in Natural and Artificial Systems. University of Mitchigan Press, 1975.
S. Kirkpatrick, C.D. Gelatt, and M.P. Vecchi. Optimization by simulated annealing. Science, 220(4598):671–680, May 1983.
Y. Linde, A. Buzo, and R.M. Gray. An algorithm for vector quanitzer design. IEEE Trans. Communications, 28:84–95, 1980.
A. Metropolis, W. Rosenbluth, M.N. Rosenbluth, H. Teller, and E. Teller. Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21(6):1087–1092, 1953.
L. Nolle. On the effect of step width selection schemes on the performance of stochastic local search strategies. In 18th European Simulation Multi-Conference, pages 149–153, 2004.
L. Nolle, D.A. Armstrong, A.A. Hopgood, and J.A. Ware. Simulated annealing and genetic algorithms applied to finishing mill optimisation for hot rolling of wide steel strip. International Journal of Knowledge-Based Intelligent Engineering Systems, 6(2):104–111, 2002.
L. Nolle, A. Goodyear, A.A. Hopgood, P.D. Picton, and N. Braithwaite. On step width adaptation in simulated annealing for continuous parameter optimisation. In Computational Intelligence-Theory and Applications, volume 2206 of Lecture Notes in Computer Science, pages 589–598. Springer, 2001.
G. Schaefer, G. Qiu, and G. Finlayson. Retrieval of palettised colour images. In Storage and Retrieval for Image and Video Databases VIII, volume 3972 of Proceedings of SPIE, pages 483–493, 2000.
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© 2006 Springer-Verlag London Limited
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Nolle, L., Schaefer, G. (2006). Hybrid search algorithm applied to the colour quantisation problem. In: Macintosh, A., Ellis, R., Allen, T. (eds) Applications and Innovations in Intelligent Systems XIII. SGAI 2005. Springer, London. https://doi.org/10.1007/1-84628-224-1_3
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DOI: https://doi.org/10.1007/1-84628-224-1_3
Publisher Name: Springer, London
Print ISBN: 978-1-84628-223-2
Online ISBN: 978-1-84628-224-9
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