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Abstract
Compression rates of fractal images are improved by applying the loss-less compression technique on the parameters of affine transformations of the fractal compressed image. By keeping PSNRs unchanged, proposed improved fractal image compression techniques give better compression rates. But, the compression time of proposed techniques are significantly increased than its counterparts. In order to solve the problem of long encoding time of fractal image compression, non-search fractal image compression coding is put forward. In this algorithm specific domain block is assigned as a matching block, so search is required and coding is accelerated. Besides, this algorithm adopts the method of range block adaptive decomposition and combination, and can solve problems like part of range blocks incapable of matching and low compression ratio of non-search method Experiments indicate that this algorithm is better than search fractal image compression algorithm and JPEG algorithm.Â
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How to Cite
Bhagyashri Pawar, P. M. B. P. R. M. (2015). Fast Fractal Image Compression Using Non Search Methodology. International Journal of Emerging Trends in Science and Technology, 2(04). Retrieved from https://ijetst.igmpublication.org/index.php/ijetst/article/view/593
References
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13. Shiping LI1, Lei Xia2, Non-search Fractal Image Compression Algorithm Research
2. Nandi, U., Mandal, J. K., “Fractal Image Compression using Fast Context Independent HV partitioning Schemeâ€, 3rd International Symposium on Electronic System Design (ISED-2012), pp. 306 – 308, December, 2012, Kolkata,India.
3. Nandi, U., Mandal, J. K., “Fractal Image Compression with Adaptive Quadtree Partitioning Schemeâ€, International Conference on Signal, Image processing and Pattern recognition (SIPP-2013), vol. 3, no. 6, pp. 289–296, 2013,Chennai, India.
4. J. Kominek, “Algorithm for fast fractal image compression,†in Proc. IS&T/SPIE 1995 Symp. Electronic Imaging: Science Technology, vol.2419, 1995.
5. Y. Fisher, et al., “Fractal Image Compression: Theory and Application â€,Springer Verlag, New York, 1995.
6. Wallace, Gregory K., : The JPEG Still Picture Compression Standard : Communications of the ACM, Volume 34, No. 4, pp 31-44 (1999).
7. Pennebaker, William B., Joan L. Mitchell, L., : JPEG Still Image Data Compression Standard : New York, Van Nostrand Reinhold (1992).
8. Fisher Y, Fractal Image Compression-Theory and Application,New York:Springer-Verlag,1995.
9. Belloulata K, Konrad J, Fractal image compression with region-based functionality. IEEE Transactions on Image Process, 4(2):351-362,2002.
10. Lai C M, Lam K M, A fast fractal image coding based on kick-out and zero contrast conditions. IEEE Transactions on Image Process, 11(2):1398-1403,2003.
11. Zhao Jian, Lei Lei, Pu Xiao-qin, Fractal theory and its application in signal processing. Bei JingTsinghua university press,57-71.2008.
12. Utpal Nandi, Jyotsna Kumar Mandal, Fractal Image Compression By Using Loss-Less Encoding On The Parameters Of Affine Transforms
13. Shiping LI1, Lei Xia2, Non-search Fractal Image Compression Algorithm Research