JACIII Vol.19 No.3 pp. 474-478
doi: 10.20965/jaciii.2015.p0474


Multiple Description Based on Fractal

Jie Yang

School of Science, Beijing Information Science and Technology University
Xiaoying DongLu No.2, Qinghe, HaiDian District, Beijing 100192, China

March 11, 2014
March 25, 2015
Online released:
May 20, 2015
May 20, 2015
fractal, multiple description, PSNR, IFS, redundancy

In this paper, I design and develop a multiple description (MD) method which is based on fractal image coding procedure. In the encoder of MD, the IFS generated mappings are separated into different parts and encoded into different descriptions so that, on each description, a subset of these mappings can be involved. Meanwhile, a desired amount of redundancy is inserted into each description such that a satisfactory reconstruction quality will be ensured. In MD decoder, the redundancy and the mappings in one description are exploited to recover the missed mappings in the other description when only one description is received. Compared with the referenced methods, the the proposed MD coder can achieve better and more robust performance under various packet loss ratio circumstance.

  1. [1]  V. K. Goyal, “Multiple description coding: compression meets the network,” IEEE Signal Processing Magazine, Vol.18, No.15, pp. 813-826, 2000.
  2. [2]  S. D. Servetto, K. Ramchandran, V. A. Vaishampayan, and K. Nahrstedt, “Multiple description wavelet based image coding,” IEEE Trans. on Image Processing, Vol.9, No.5, pp. 813-826, 2000.
  3. [3]  C. Lin, T. Tillo, and Y. Zaho, “Multiple description coding for H.264/AVC with redundancy allocation at macro block level,” IEEE Trans. on Circuits and Systems for Video Technology, Vol.21, No.5, 2011.
  4. [4]  J. Chen, “Vector Gaussian multiple description coding with individual and central distortion constraints,” IEEE Int. Symp. on ISIT, pp. 1693-1697, 2011.
  5. [5]  Q. Guo, “Research of DSR Routing Technology in Vehicle Ad Hoc Network Based on Multiple Description Coding and Distance,” Advances in Information Sciences and Service Sciences, Vol.4, No.6, pp. 111-118, 2012.
  6. [6]  L. Wang, M. N. S. Swamy, and M. O. Ahmad, “Multiple description image coding using pixel interleaving and wavelet transform,” The 2002 45th Midwest Sym. on circuits and systems (MWSCAC-2002), Vol.2, pp. 235-238, 2002.
  7. [7]  G. Olmo and T. Tillo, “Directional multiple description scheme for still images,” Proc. of the 2003 10th IEEE Int. Conf. Electronics, Circuits and Systems (ICECS 2003), Vol.2, pp. 14-17, 2003.
  8. [8]  Y. Wang, M. Orchard, V. Vaishampayan, and A. Reibman, “Multiple description coding using pairwise correlation transforms,” IEEE Trans. on Image Processing, Vol.10, No.3, pp. 351-366, 2001.
  9. [9]  Z. Zhang and Y. Zhao, “Multiple description image coding based on fractal,” Int. J. of Innovative Computing, Information and Control, Vol.3, No.6, pp. 1615-1623, 2007.
  10. [10]  L. Meiqin, Z. Yao, Q. Junpeng, and D. Xia, “Multiple description image coding based on fast fractal coding,” 4th IET Int. Conf. on Wireless, Mobile & Multimedia, pp. 257-261, 2011.
  11. [11]  Y. Fisher, “Fractal Image Compression: Theory and Application,” Springer-Verlag, 1994.
  12. [12]  C. Fan, “Speeding up Search Algorithm Based on Local similarity,” J. of Convergence Information Technology, Vol.7, No.21, pp. 135-141, 2012.
  13. [13]  Y. H. Noh, S. H. Kim, and N. C. Kim, “Block loss recovery using fractal extrapolation for fractal coded images,” Int. Conf. on Image Processing (ICIP), Vol.1, pp. 751-755, 1998.
  14. [14]  P. Salama, N. B. Shroff and E. J. Delp, “Error concealment technique for encoded video streams,” Int. Conf. on Image Processing (ICIP), Vol.1, pp. 9-12, 1995.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Mar. 24, 2017