Home   >   CSC-OpenAccess Library   >    Manuscript Information
Fractal Image Compression of Satellite Color Imageries Using Variable Size of Range Block
Veenadevi.S.V, A G Ananth
Pages - 1 - 8     |    Revised - 20-01-2014     |    Published - 11-02-2014
Volume - 8   Issue - 1    |    Publication Date - February 2014  Table of Contents
Maximum Range Block Size (R max ), Minimum Range Block Size (R min ), Affine Transformation, Canonical Classification, PSNR (Peak Signal to Noise Ratio), CR (Compression Ratio).
Fractal image compressions of Color Standard Lena and Satellite imageries have been carried out for the variable size range block method. The image is partitioned by considering maximum and minimum size of the range block and transforming the RGB color image into YUV form. Affine transformation and entropy coding are applied to achieve fractal compression. The Matlab simulation has been carried out for three different cases of variable range block sizes. The image is reconstructed using iterative functions and inverse transforms. The results indicate that both color Lena and Satellite imageries with R max = 16 and R min = 8, shows higher Compression ratio (CR) and good Peak Signal to Noise Ratios (PSNR). For the color standard Lena image the achievable CR~13.9 and PSNR ~25.9 dB, for Satellite rural image of CR~ 16 and PSNR ~ 23 and satellite urban image CR~16.4 and PSNR~16.5. The results of the present analysis demonstrate that, for the fractal compression scheme with variable range method applied to both color and gray scale Lena and satellite imageries, show higher CR and PSNR values compared to fixed range block size of 4 and 4 iterations. The results are presented and discussed in the paper.
CITED BY (1)  
1 Kodgule, U. B., & Sonkamble, B. A. (2015). Discrete Wavelet Transform based Fractal Image Compression using Parallel Approach. International Journal of Computer Applications, 122(16).
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
A. Selim, M. M. Hadhoud, M. I. Dessouky and F. E. Abd El-Samie, “A Simplified Fractal Image Compression Algorithm”, IEEE Computer Engineering & Systems, ICCES, PP.53-58,2008.
Arnaud E.Jacquin, “Image coding based on a fractal theory of iterated contractive image transformations”, IEEE Transaction on Image processing, PP.18-30, 1992.
Bohong Liu and Yung Yan, “An Improved Fractal Image Coding Based on the Quadtree”,IEEE 3rd International Congress in Image and Signal Processing, Vol 2, PP.529-532, 2010.
Brendt Wohlberg and Gerhard de Jager, “A Review of the Fractal Image Coding Literature”,IEEE Transaction on Image Processing, Vol 8, PP. 1716-1729, 1999.
Dietmar Saupe,”Accelerating Fractal Image Compression by Multi Dimensional Nearest Neighbor Search”, IEEE Data Compression, PP.222-231, 1995.
Dr. Muhammad Kamran, Amna Irshad Sipra and Muhammd Nadeem, “A novel domain optimization technique in Fractal image Compression”, IEEE Proceedings of the 8th world Congress on Intelligent Control and Automation, PP.994-999, 2010.
G.Lu and T.L.Yew, “Applications of Partitioned Iterated Function Systems in Image and Video Compression”, Journal of Visual Communication and Image Representation, Vol 7,PP.144-154, 1996.
Hannes Hartenstein, Associate Member, IEEE, Matthias Ruhl, and Dietmar Saupe,” RegionBased Fractal Image Compression”, IEEE transactions on Image processing, vol. 9, no. 7,July 2000.
Hui Yu, Li, Hongyu Zhai, Xiaoming Dong, “Based on Quadtree Fractal Image Compression Improved Algorithm for Research”, International Conference on E-product E-service and EEntertainment,PP.1-3, 2010.
Lester Thomas and Farzin Deravi ,” Region-Based Fractal Image Compression Using Heuristic Search”, IEEE transactions on Image processing, vol. 4, no. 6, June 1995.
M. Barnsley, “Fractals Everywhere”, San Diego Academic Press, 2nd Edition, 1993.
Mario Polvere and Michele Nappi, “Speed-Up In Fractal Image Coding: Comparison of Methods”, IEEE Transaction on Image Processing, Vol. 9, No. 6, PP. 1002-1009, 2000
Sumathi Poobal, G.Ravindran, “Analysis on the Effect of Tolerance Criteria in Fractal Image Compression” IEEE IST 2005 International Workshop on Imaging Systems and Techniques,PP.119-124, 2005.
VeenaDevi.S.V and A.G.Ananth, “Fractal Image Compression of Satellite Imageries Using Variable Size of Range Block”, IEEE International Conference on Signal and Image Processing Applications, 2013.
VeenaDevi.S.V and A.G.Ananth, “Fractal Image Compression of Satellite Imageries”, IJCA,Vol 30, No.3, PP.33-36, 2011.
Y.Fisher, “Fractal Image Compression: Theory and Application”, Springer-Verlag, 1995.
Yung-Gi, wu, Ming-Zhi, Huang, Yu-Ling, Wen,”Fractal Image Compression with variance and mean”, IEEE International Conference on Multimedia and Expo, Volume 1, PP.353-356,2003.
Zhuang Wu, Bixi Yan, “An effective Fractal image Compression Algorithm”, IEEE international Conference on ICCASM, Vol.7, PP.139-143, 2010.
Mr. Veenadevi.S.V
R V College of Engineering - India
Dr. A G Ananth
R V College of Engineering - India

View all special issues >>