Commenced in January 2007
Paper Count: 31093
Hybrid Genetic-Simulated Annealing Approach for Fractal Image Compression
Abstract:In this paper a hybrid technique of Genetic Algorithm and Simulated Annealing (HGASA) is applied for Fractal Image Compression (FIC). With the help of this hybrid evolutionary algorithm effort is made to reduce the search complexity of matching between range block and domain block. The concept of Simulated Annealing (SA) is incorporated into Genetic Algorithm (GA) in order to avoid pre-mature convergence of the strings. One of the image compression techniques in the spatial domain is Fractal Image Compression but the main drawback of FIC is that it involves more computational time due to global search. In order to improve the computational time along with acceptable quality of the decoded image, HGASA technique has been proposed. Experimental results show that the proposed HGASA is a better method than GA in terms of PSNR for Fractal image Compression.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1332652Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1362
 A.E.Jacquin, ÔÇÿImage coding Based on a Fractal theory of Iterated contractive Image Transformations,- IEEE Transactions on Image Processing. vol 1, Jan 92, pp 18-30
 A.E.Jacquin, "Fractal Image coding: A Review," Proc. IEEE, vol 81, pp. 1451-1465, 1993.
 M.F.Barnsley, Fractals Everywhere. New York: Academic 1988.
 M.F Barnsley and A.E Jacquin, "Application of recurrent iterative function systems to images", Proc SPIE, 1001(3),122-131 (1998)
 Mingshui Li, Shanhu Ou and Heng Zhang, "The new progress in research approach of fractal image compression" journal of engineering graphics, 4(3), 2004, pp 143-152 .
 Xiaoping Wang, Liming Cao, "Genetic Algorithms-theory, application and software reliability Xi" An Jiao Tong University Press (2002).
 David Goldberg, "Genetic algorithms in search, optimization and machine learning" Addison-Wesley Publishing Company: MA (1989).
 Kalyanmoy Deb, "Optimization for engineering design" Prentice Hall of India,2000.
 Y.Chakrapani, K.Soundera Rajan, "A comparative approach to fractal image compression using genetic algorithm and simulated annealing technique" Asian Journal of Information technology 7(7), pp 285-289.
 M.Hassaballah, M.M.Makky, Youssuf B. Mahdy, "A fast fractal image compression method based entropy" Electronic letters on computer vision and image analysis, 5(I) 2005, pp 30-40.
 Zhang Chao, Zhou Yiming, Zhang Zengke, "Fast fractal image encoding based on special image features" Journal of Tsinghua science and technology, Vol12, No 1, 2007,pp 58-62