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Randomized Algorithm for Scaling Factors in Fractal Image Compression
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 41 - Number 7 |
| Year of Publication: 2012 |
| Authors: Dinesh Rao B, Ganesh Kamath, Niranjan U C |
10.5120/5553-7624
|
Dinesh Rao B, Ganesh Kamath, Niranjan U C . Randomized Algorithm for Scaling Factors in Fractal Image Compression. International Journal of Computer Applications. 41, 7 ( March 2012), 19-22. DOI=10.5120/5553-7624
Abstract
Modern fractal compression methods are based on iterative function systems (IFS), which was developed by Barnsley [1] and Jacquin [2]. During compression, the algorithm partitions the image into a set of square blocks (domain blocks). After this a new partition is made into smaller range blocks [2]. The domain blocks are generally double the size of range blocks. For every range block the nearest domain block is identified among all domain blocks after applying a set of transformations on the domain blocks. Smaller sized images are obtained by storing the information about these transformations alone. The transforms store the domain number, scaling constant, offset etc. This method of compression is called the partitioned iteration function system (PIFS). This paper explores the use of variable scaling factors for the transformation from domain to the range blocks. This variable factor has been generated using a pseudo-random number generator. The results show comparable ratios of compression and RMS error with PIFS (Partitioned iterated function systems) based fractal compression.
References
- M. F. Barnsley and L. P. Huard, "Fractal Image Compression", AK Peters. Ltd. (1992).
- Ning Lu, Fractal Imaging, Academic Press, 1997.
- Arnaud E. Jacquin, "Fractal Image Coding: A Review", Proceeding of the IEEE, Vol. 81, No. 10, October 1993.
- Dan C. Popescu, Alex Dimca, and Hong Yan, "A Nonlinear Model for Fractal Image Coding", IEEE Transaction on image processing, Vol. 6, No. 3, March 1997.
- Zhuang Wu, Bixi Yan, "An effective fractal image compression algorithm", IEEE International conference on ICCASM, 2010, pp. 139-143.
- Hosseini, Shookooh, Shahhosseini, Beizaee, "Speeding up fractal image de-compression", IEEE International conference on ICCAIE, 2010, pp. 521-526.
- Hui Yu, Li Li, Dan Liu, HongyuZhai, Xiaoming Dong, "Based on Quadtree Fractal Image Compression Improved Algorithm for Research", IEEE Trans, 2010, pp. 1-3.
- Dinesh Rao B. , Ganesh Kamath and Arpitha K. J. "Difference based Non-linear Fractal Image Compression". International Journal of Computer Applications 38(1):41-44, January 2012. Published by Foundation of Computer Science, New York, USA.
- T. K Truong, C. M Kung, , J. H Jeng, M. L Hsieh, "Fast fractal image compression using spatial correlation", ScienceDirect, Vol 22, Issue 5, December 2004, Pages 1071–1076.
- Yung-Gi Wu, Ming-Zhi Huang, Yu-Ling Wen, "Fractal image compression with variance and mean", IEEE, vol. 1, 18 August 2003.
- S. K. Ghosh, Jayanta Mukherjee, P. P. Das, "Fractal image compression: a randomized approach", Pattern Recognition Letters archive, Volume 25 Issue 9, 2 July 2004, Elsevier Science Inc. New York, NY, USA.
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