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Discrete Wavelet Transform based Fractal Image Compression using Parallel Approach

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 122 - Number 16
Year of Publication: 2015
Authors:
Umesh B. Kodgule
B A. Sonkamble
10.5120/21785-5068

Umesh B Kodgule and B A Sonkamble. Article: Discrete Wavelet Transform based Fractal Image Compression using Parallel Approach. International Journal of Computer Applications 122(16):18-22, July 2015. Full text available. BibTeX

@article{key:article,
	author = {Umesh B. Kodgule and B A. Sonkamble},
	title = {Article: Discrete Wavelet Transform based Fractal Image Compression using Parallel Approach},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {122},
	number = {16},
	pages = {18-22},
	month = {July},
	note = {Full text available}
}

Abstract

Fractal based technique for compression is one of the popular methods for compression of videos and images. It has generated much interest due to its promise of high compression ratios at good decompression quality and it enjoys the advantage of very fast decompression and resolution independent decoding . But it suffers from highly computationally intensive encoding process which makes it unsuitable for real time applications. Many approaches have been suggested but they do not satisfy the requirement of low encoding time and high quality reconstructed images. In this paper parallel algorithm for fractal image compression using NVIDIA`s GPGPU is proposed. Also novel discrete wavelet transform based feature detection is used to reduce the number of block comparisons. Experimental results show significant reduction in encoding time and quality of reconstructed images is also good compared to other approaches making this technique suitable for real time applications such as image retrieval, image denoising, Image authentication and encryption, satellite and medical imaging.

References

  • Barnsley, Michael F. Fractals everywhere. Academic press, 2014.
  • Fisher, Yuval. Fractal compression: Theory and application to digital images. Springer Verlag, New York, 1994.
  • Jacquin, Arnaud E. "Image coding based on a fractal theory of iterated contractive image transformations," IEEE Transactions on Image Processing, vol. 1, no. 1, pp. 18-30, Proc. IEEE, 1992
  • Jacobs, EW and Fisher, Yuval and Boss, RD,"Image compression: A study of the iterated transform method," Journal of signal processing, vol. 29, no. 3, pp. 251-263, Elsevier, 1992.
  • Hassaballah, Makky and Mahdy, Youssef B and Makky, MM. "A fast fractal image compression method based entropy," in ELCVIA: electronic letters on computer vision and image analysis, vol. 5, pp. 30-40, 2005.
  • Wang, Hai. "Fast image fractal compression with graph-based image segmentation algorithm", International Journal of Graphics, vol. 1, no. 1, pp. 19-28, 2010.
  • Kung, CM and Yang, WS and Ku, CC and Wang, CY. " Fast fractal image compression base on block property, "in IEEE 2008 International Conference on Advanced Computer Theory and Engineering, Phuket, DEC, 2008,pp. 477-481
  • Chen, Hsiu-Niang and Chung, Kuo-Liang and Hung, Jian-Er. " Novel fractal image encoding algorithm using normalized one-norm and kick-out condition", Journal of Image and Vision Computing, vol. 28, no. 3, pp. 518-525, Elsevier, 2010.
  • Palazzari, Paolo and Coli, Moreno and Lulli, Guglielmo. " Massively parallel processing approach to fractal image compression with near-optimal coefficient quantization, "Journal of systems architecture, vol. 45, no. 10, pp. 765-779, Elsevier, 1999.
  • Furao, Shen and Hasegawa, Osamu. "A fast no search fractal image coding method", Journal of Signal Processing: Image Communication, vol. 19,no. 5,pp. 393-404,Elsevier,2004.
  • Zhang, Yi and Wang, Xingyuan. "Fractal compression coding based on wavelet transform with diamond search, "journal of Nonlinear Analysis: Real World Applications, vol. 13, no. 1, pp. 106-112, Elsevier, 2012.
  • Md. Enamul Haque, Abdullah Al Kaisan, Mahmudur R. Saniat, Aminur Rahman. " GPU Accelerated Fractal Image Compression for Medical Imaging in Parallel Computing Platform, "Journal of CORR, vol. abs/1404. 0774, 2014.
  • Chauhan, Munesh Singh and Negi, Ashish and Rana, Prashant Singh. " Fractal image compression using dynamically pipelined GPUclusters,"Proceedings of the Second InternationalConference on Soft Computing for Problem Solving (SocProS 2012), Dec, 2012, pp. 575-581.
  • Wang, Jianji and Zheng, Nanning. "A novel fractal image compression scheme with block classification and sorting based on Pearson's correlation coefficient,"IEEE Transactions on Image Processing, vol. 22, no. 9, pp. 3690-3702, Proc. IEEE, 2013.
  • Ananth, AG. " Fractal Image Compression of Satellite Color Imageries Using Variable Size of Range Block,"International Journal of Image Processing (IJIP), vol. 8, no. 1, pp. 1-8, 2014.
  • Jacob Toft Pedersen. "Parallel fractal compression for medical imaging. " Parallel Computing For Medical Imaging and Simulation, 2010.
  • Berke, Jozsef. " Comparison and Application Possibilities of JPEG and Fractal-based Image Compressing Methods in the Development of Multimedia Based Material, "in proc. 1999 Data Compression Conference, pp. 517-525, 1999.
  • Chaudhari, RE and Dhok, SB. "Review of Fractal Transform based Image and Video Compression, "International Journal of Computer Applications, vol. 57, no. 19, pp. 23-32, Citeseer, 2012.
  • Chaurasia, Vijayshri and Somkuwar, Ajay. "Review of a novel technique: fractal image compression," International Journal on Emerging Technologies, vol. 1, no. 1, pp. 53-56, 2010.
  • Wohlberg, Brendt and De Jager, Gerhard. "A review of the fractal image coding literature,"IEEE Transactions on Image Processing, vol. 8, no. 12, pp. 1716-1729, IEEE, 1999.