A Hybrid Method on Fractal Image Compression Using Quadtree Decomposition and Run length Encoding
International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC).
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Fractal image compression is a relatively recent image compression method which exploits similarities in different parts of the image. Fractal Image compression (FIC) is one among the compression techniques in the spatial domain which exploits similarities in different parts of the image. One can see the self similar regions in the image above. In this paper we discuss about the two methods combined and form a one method. By using threshold value of 0.2 and Runlength Encoding for encoding and decoding of the image these techniques have been applied for the compression of satellite imageries. The compression ratio (CR) and Peak Signal to Noise Ratio (PSNR) values are determined. The Matlab simulation results show that for the Quad tree decomposition approach shows very significant improvement in the compression ratios and PSNR values derived from the fractal compression with range block and iterations technique.
 A. El-Harby α & G. M. Behery,” Novel Color Image Compression Algorithm Based on Quad tree”, Global Journal of Computer Science and Technology Graphics & Vision Volume 12 Issue 13 Version 1.0 Year 2012
 Sankaragomathi, L. Ganesan, and S. Arumugam, “Fractal Image Compression Applied to Remote Sensing”, World Academy of Science, Engineering and Technology 11 2007
 Roshni S. Khedgaonkar, Shailesh D. Kamble, “Application of Quadtree Partitioning in Fractal Image Compression using Error Based Approach, IOSR Journal of Engineering (IOSRJEN) www.iosrjen.org ISSN : 2250-3021 Vol. 2 Issue 1, Jan.2012, pp. 050-054
 Ruhiat Sultana, Nisar Ahmed, Shaik Mahaboob Basha,” Advanced Fractal Image Coding Based on the Quadtree”, Computer Engineering and Intelligent SystemsISSN 2222-1719 (Paper) ISSN 2222-2863 (Online)Vol 2, No.3,
 Tong Chong Sze,” Fast Fractal Image Encoding Based on Adaptive”,Search IEEE Transactions on Image Processing, 2001, 10(9):933-942.
 Saupe D, RuhlM, “Evolutionary Fractal Image Compression[OB/OL],http://www.inf.uni.ko nstanz.de/cgip/bib/files/SaRu96.pdf, 2004.
 Distasi R, Nappi M, Riccio D,”A range/domain approximation error-based approach for fractal image Compression”,IEEE Transactions on Image Processing, 2006, 15(1):89-97.
 Erjun Zhao, Dan Liu. Fractal image compression methods a review,Proceedings of the Third Sonal, D.Kumar,”A Study of Various Image Compression Technique”.
 M.F. Barnsley and A.E. Slaon, “A better way to compress image, ” BYTE Magazine., January 1988.
 C. S. Tong and W. Man, “Adaptive Approximation Nearest Neighbor Search for Fractal Image Compression,”IEEE Transactions on Image Processing,” vol. 11, No. 6, pp. 605-615, 2002.
 B. Wohlberg and Gerhard de Jager,”A review of the Fractal Image Compression Literature,” IEEE Transactions on Image Processing, vol. 8, No. 12, pp. 1716-1729, Dec. 1999
 Yung-Kuan Chan (2004) "Block image retrieval based on a compressed linear quadtree", Image and Vision Computing, Vol. 22(5), pp. 391-397.