Skip to main content

Quad-Tree Based Adaptive Wavelet Packet Image Coding

  • Chapter
  • First Online:
Trends in Communication Technologies and Engineering Science

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 33))

Abstract

In wavelet domain, if a wavelet coefficient is insignificant, the spatially related wavelet coefficients taken from all the successively higher frequency subbands of the same orientation are likely to be insignificant. This chapter will present quad-tree based adaptive wavelet packet transform in conjunction with the above-mentioned rearrangement scheme to generate adaptive wavelet packet trees (AWPT). We particularly combine SPIHT with AWPT, which is named set partitioning in adaptive wavelet packet trees (SPIAWPT), for image compression.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. H. G. Musmann, P. Pirsch, and H. J. Grallert, “Advances in Picture Coding,” Proc. IEEE, vol. 73, pp. 523–548, April, 1985.

    Article  Google Scholar 

  2. R. J. Clarke, Transform Coding of Images, New York: Academic Press, 1985.

    Google Scholar 

  3. O. J. Kwon and Rama Chellappa, “Region Adaptive Subband Image Coding,” IEEE Trans. On Image Processing, vol. 7, no. 5, pp. 632–648, May, 1988.

    Article  Google Scholar 

  4. K. R. Rao and J. J. Hwang, Techniques and Standards for Image, Video and Audio Coding, Englewood Cliffs: Prentice Hall, 1996.

    Google Scholar 

  5. W. B. Pennebaker and J. L. Mitchell, JPEG Still Image Data Compression Standards, New York: Van Nostrand, 1993.

    Google Scholar 

  6. M. Antonini, M. Barlaud, P. Mathieu, and I. Daubechies, “Image Coding Using Wavelet Transform,” IEEE Trans. On Image Processing, vol. 1, pp. 205–220, April, 1992.

    Article  Google Scholar 

  7. G. Strang and T. Nguyen, “Wavelets and Filter Banks,” Wellesley-Cambridge, Wellesley, MA., USA, 1996.

    Google Scholar 

  8. J. M. Shapiro, “Embedded Image Coding Using Zero-Trees of Wavelet Coefficients,” IEEE Trans. On Signal Processing, vol. 40, pp. 3445–3462, 1993.

    Article  Google Scholar 

  9. A. Said and W. A. Pearlman, “A New, Fast, and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees,” IEEE Trans. On Circuits Syst. Video Tech. vol. 6, pp. 243–250, 1996.

    Article  Google Scholar 

  10. D. Mukherjee and S. K. Mitra, “Vector SPIHT for Embedded Wavelet Video and Image Coding,” IEEE Trans. On Circuits Syst. Video Tech. vol. 13, pp. 231–246, March, 2003.

    Article  Google Scholar 

  11. A. Said and W. A. Pearlman, “Low Complexity Waveform Coding via Alphabet and Sample-Set Partitioning,” Proc. SPIE Visual Communications and Image Processing, vol. 3024, pp. 25–37, Feb., 1997.

    Google Scholar 

  12. J. Andrew, “A Simple and Efficient Hierarchical Image Coder,” Proc. IEEE Int. Conf. Image Processing (ICIP), vol. 3, pp. 658–661, Oct., 1997.

    Article  Google Scholar 

  13. W. A. Pearlman, A. Islam, N. Nagaraj, and A. Said, “Efficient, Low Complexity Image Coding With a Set-Partitioning Embedded Block Coder,” IEEE Trans. On Circuits Syst. Video Tech. vol. 14, pp. 1219–1235, Nov., 2004.

    Article  Google Scholar 

  14. D. Taubman, “High Performance Scalable Image Compression with EBCOT,” IEEE Trans. On Image Processing, vol. 9, pp. 1158–1170, July, 2000.

    Article  Google Scholar 

  15. A. Skodras, C. Christopoulos, and T. Ebrahimi, “The JPEG 2000 still image compression standard,” IEEE Signal Process. Mag., vol. 18, pp. 36–58, September, 2001.

    Article  Google Scholar 

  16. H.-C. Fang, Y.-W. Chang, T.-C. Wang, C.-T. Huang, and L.-G. Chen, “High-Performance JPEG 2000 Encoder with Rate-Distortion Optimization,” IEEE Trans. On Multimedia, vol. 8, no. 4, pp. 645–653, August. 2006.

    Article  Google Scholar 

  17. F. G. Meyer, A. Z. Averbuch, and J.-O. Stromberg,” Fast Adaptive Wavelet Packet Image Compression,” IEEE Trans. Image Processing, vol. 9, pp. 792–800, 2000.

    Article  Google Scholar 

  18. D. Engle, A. Uhl, “Adaptive Object Based Image Compression Using Wavelet Packets,” VIPromCom-2002, 4th EURASIP, IEEE Region 8 International Symposium on Video/Image Processing and Multimedia Communications, pp. 183–187, 2002.

    Google Scholar 

  19. N. M. Rajpoot, R. G. Wilson, F. G. Meyer and R. R. Coifman, “Adaptive Wavelet Packet Basis Selection for Zerotree Image Coding,” IEEE Trans. On Image Processing, Vol. 12, pp. 1460–1472, 2003.

    Article  MathSciNet  Google Scholar 

  20. K. Ramchandran and M. Vetterli “Best Wavelet Packet Bases in A Rate Distortion Sense,” IEEE Trans. On Image Processing, vol. 2, pp. 160–175, 1993.

    Article  Google Scholar 

  21. Z. Xiong, K. Ramchandran, and M. Orchard, “Wavelet Packet Image Coding Using Space-Frequency Quantization,” IEEE Trans. On Image Processing, vol. 7, pp. 892–898, 1998.

    Article  Google Scholar 

  22. N. M. Rajpoot, R. G. Wilson, F. G. Meyer and R. R. Coifman, “Adaptive Wavelet Packet Basis Selection for Zerotree Image Coding,” IEEE Trans. On Image Processing, vol. 12, pp. 1460–1472, 2003.

    Article  MathSciNet  Google Scholar 

  23. N. Sprljan, S. Grgic and M. Grgic, “Modified SPIHT Algorithm for Wavelet Packet Image Coding,” Real-Time Imaging, vol. 11, pp. 378–388, 2005.

    Article  Google Scholar 

  24. T.-Y. Sung and H.-C. Hsin, “An Efficient Rearrangement of Wavelet Packet Coefficients for Embedded Image Coding Based on SPIHT Algorithm,” IEICE Trans. Fundamentals, vol. E90-A, no. 9, pp. 2014–2020, 2007.

    Article  Google Scholar 

  25. H.-C. Hsin and T.-Y. Sung, “Image Coding with Adaptive Wavelet Packet Trees,” IMECS 2008, Hong Kong, (The Certificate of Merit).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media B.V

About this chapter

Cite this chapter

Sung, TY., Hsin, HC. (2009). Quad-Tree Based Adaptive Wavelet Packet Image Coding. In: Wai, PK., Huang, X., Ao, SI. (eds) Trends in Communication Technologies and Engineering Science. Lecture Notes in Electrical Engineering, vol 33. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9532-0_10

Download citation

  • DOI: https://doi.org/10.1007/978-1-4020-9532-0_10

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-9492-7

  • Online ISBN: 978-1-4020-9532-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics