ICTACT Journal on Image and Video Processing

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Fractal Compression Technique for Color Images Using Variable Block


Affiliations
1 Department of Electronics and Communication Engineering, Mewar University, India
2 Department of Electronics and Communication Engineering, Nawab Shah Alam Khan College of Engineering and Technology, India
     

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The main intention of Fractal Image Compression is to reduce the size of image and maintain good level of their reconstructed image. A major issue in Fractal Image Compression is decrease in image quality, compression ratio and PSNR. To overcome these issues we employ Fractal transformation with entropy coding. There are two phases in the proposed approach. In the first phase color images are separated into three RGB planes using variable range block size. In second phase by applying the inverse transform and iterative functions the image is restored. It is observed that the results are improving in fractal compression for both gray images as well as color images. In this work high CR and PSNR is observed compared to fixed block range and other existing methods. The proposed work yields better CR of 20 and high PSNR.

Keywords

Fractal Image Compression, Variable Block Size, CR, PSNR.
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  • Gagnpreet Kaur, Hitashi Hitashi and Gurdev Singh, “Performance Evaluation of Image Quality based on Fractal Image Compression”, International Journal of Computers and Technology, Vol. 2, No.1, pp. 20-27, 2012.

  • Zhuang Wu and Bixi Yan, “An Effective Fractal Image Compression Algorithm”, Proceedings of IEEE International Conference on Computer Application and System Modeling, pp. 139-143, 2010.

  • Sumathi Poobal and G.Ravindran, “Analysis on the Effect of Tolerance Criteria in Fractal Image Compression”, Proceedings of IEEE International Workshop on Imaging Systems and Techniques, pp. 119-124, 2005.

  • A. Selim, M.M. Hadhoud, M.I. Dessouky and F.E. Abd El-Samie, “A Simplified Fractal Image Compression Algorithm”, Proceedings of IEEE International Conference on Computer Engineering and Systems, pp. 53-58, 2008.

  • Dietmar Saupe, “Accelerating Fractal Image Compression by Multi-Dimensional Nearest Neighbor Search”, Proceedings of IEEE Data Compression, pp. 222-231, 1995.

  • Arnaud E. Jacquin, “Image Coding based on a Fractal Theory of Iterated Contractive Image Transformations”, IEEE Transaction on Image Processing, Vol. 1, No. 1, pp. 18-30, 1992.

  • M. Barnsley, “Fractals Everywhere”, 2nd Edition, San Diego Academic Press, 1993.

  • Y. Fisher, “Fractal Image Compression: Theory and Application”, Springer, 1995.

  • Brendt Wohlberg and Gerhard De Jager, “A Review of the Fractal Image Coding Literature”, IEEE Transactions on Image Processing, Vol. 8, No. 12, pp. 1716-1729, 1999.

  • Guojun Lu and Toon Lin Yew, “Applications of Partitioned Iterated Function Systems in Image and Video Compression”, Journal of Visual Communication and Image Representation, Vol. 7, No. 2, pp. 144-154, 1996.

  • Douda Sofia, Bagri Abdallah, Abdel Hakim and Amer Elimrani, “A Reduced Domain Pool based on DCT for a Fast Fractal Image Encoding”, Electronic Letters on Computer Vision and Image Analysis, Vol. 10, No. 1, pp. 1123, 2011

  • Vahdati Gohar, Khodadadi Habib, Yaghoobi Mahdi and Akbarzadeh-T Mohammad, “Fractal Image Compression Based on Spatial Correlation and Hybrid Particle Swarm Optimization with Genetic Algorithm”, Proceedings of 22nd International Conference on Software Technology and Engineering, pp. 134-138, 2010.

  • G.K. Kharate and V.H. Patil, “Color Image Compression Based on Wavelet Packet Best Tree”, International Journal of Computer Science Issues, Vol. 7, No. 2, pp. 31-35, 2010.

  • D. Venkatasekhar and P . Aruna, “A Fast Fractal Image Compression using Huffman Coding”, Asian Journal of Computer Science and Information Technology, Vol. 2, No. 9, pp. 272-275, 2012.

  • M. Khalil, “Image Compression using New Entropy Coder”, International Journal of Computer Theory and Engineering, Vol. 2, No. 1, pp. 39-42, 2010.

  • Fractal Image Compression, Available at: http://www.math.psu.edu/tseng/class/Fractals.html.

  • Michael Barnsley and Lyman Hurd, “Fractal Image Compression”, AK Peters Limited, 1992.

  • A.R. Nadira Banu Kamal and P. Priyanga, “Iteration Free Fractal Compression using Genetic Algorithm for Still Colour Images”, ICTACT Journal on Image and Video Processing, Vol. 4, No. 3, pp. 785-790, 2014.

  • Mohammed Ismail and S.M. Basha, “Improved Fractal Image Compression using Range Block Size”, Proceedings of IEEE International Conference on Computer Graphics, Vision and Information Security, pp. 284-289, 2015.

  • S.V. Veena Devi, A.G. Ananth, “Fractal Image Compression of Satellite Imageries using Variable Size of Range Block”, Proceedings of IEEE International Conference on Signal and Image Processing Applications, pp. 172-175, 2013.

  • Mario Polvere and Nappi Michele, “Speed-Up in Fractal Image Coding: Comparison of Methods”, IEEE

  • Transaction on Image Processing, Vol. 9, No. 6, pp. 10021009, 2000.

  • A.H. Husseen, S.Sh. Mahmud and R.J. Mohammed, “Image Compression using Proposed Enhanced Run Length Encoding Algorithm”, Ibn AL- Haitham Journal for Pure and Applied Science, Vol. 24, No. 1, pp. 18-25, 2011.

  • K. Sharmila and K. Kuppusamy, “A New Color Image Compression Based on Fractal and Discrete Cosine Transform”, International Journal of Engineering and Computer Science, Vol. 3, No. 7, pp. 7054-7057, 2014.

  • S.V. Veenadevi and A.G. Ananth, “Fractal Image Compression of Satellite Color Imageries using Variable Size of Range Block”, International Journal of Image Processing, Vol. 8, No. 1, pp. 1-8, 2014.


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  • Fractal Compression Technique for Color Images Using Variable Block

Abstract Views: 194  |  PDF Views: 6

Authors

Nisar Ahmed
Department of Electronics and Communication Engineering, Mewar University, India
Syed Abdul Sattar
Department of Electronics and Communication Engineering, Nawab Shah Alam Khan College of Engineering and Technology, India

Abstract


The main intention of Fractal Image Compression is to reduce the size of image and maintain good level of their reconstructed image. A major issue in Fractal Image Compression is decrease in image quality, compression ratio and PSNR. To overcome these issues we employ Fractal transformation with entropy coding. There are two phases in the proposed approach. In the first phase color images are separated into three RGB planes using variable range block size. In second phase by applying the inverse transform and iterative functions the image is restored. It is observed that the results are improving in fractal compression for both gray images as well as color images. In this work high CR and PSNR is observed compared to fixed block range and other existing methods. The proposed work yields better CR of 20 and high PSNR.

Keywords


Fractal Image Compression, Variable Block Size, CR, PSNR.

References