Skip to main content
Log in

AND-OR tree-based mode selection for video coding

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

The conventional video coding approach is pragmatic in that researchers design different methods and compare their results to state-of-the-art methods. Although the H.264/AVC baseline is effective, there is a need to develop an abstract view of video coding, in the hope that new insights can be derived from the abstraction. In this paper, we propose a preliminary approach based on an AND-OR tree representation of video coding. We show that the H.264/AVC baseline can be represented as an AND-OR tree structure. Based on the AND-OR tree representation, we propose two video coding systems: one is a T+2D wavelet codec based on a motion-compensated temporal filtering (MCTF) lifting structure, and the other is the AND-OR tree implementation of the H.264/AVC baseline. We also compare the proposed systems’ coding performance in terms of the PSNR with that of H.264/AVC JM 16.2.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. http://diracvideo.org/

  2. Cheng C.-C., Peng G.-J., Hwang W.-L.: Subband weighting with pixel connectivity for 3-D wavelet coding. IEEE Trans. Image Process. 18(1), 52–62 (2009)

    Article  MathSciNet  Google Scholar 

  3. Hsiang S.-T., Woods J.W.: Embedded video coding using invertible motion compensated 3D subband/wavelet filter bank. Signal Process. Image Commun. 16, 705–724 (2001)

    Article  Google Scholar 

  4. Lee, T.-H.J., Hwang, W.-L.: Mode selection and optimal rate control for video coding using an ANR-OR tree representation. In: IEEE International Conference on Image Processing, pp. 449–452. (2007)

  5. Luo, L., Li, J., Li, S., Zhuang, Z., Zhang, Y.-Q.: Motion compensated lifting wavelet and its application in video coding. In: IEEE International Conference on Multimedia and Expo, pp. 365–368 (2001)

  6. Moecke M., Seara R.: Sorting rates in video encoding process for complexity reduction. IEEE Trans. Circ. Syst. Video Technol. 20, 88–101 (2010)

    Article  Google Scholar 

  7. Narendra P.M., Fukunaga K.: A branch and bound algorithm for feature subset selection. IEEE Transactions on Computers 26(9), 917–922 (1977)

    Article  MATH  Google Scholar 

  8. Nils N.J.: Principles of Artificial Intelligence. Springer, Berlin (1983)

    Google Scholar 

  9. Ohm J.-R.: Three-dimensional subband coding with motion compensation. IEEE Trans. Image Process. 3(5), 559–571 (1994)

    Article  Google Scholar 

  10. Ohm J.-R., Van der Schaar M., Woods J.W.: Interframe wavelet coding motion picture representation for universal scalability. Signal Process. Image Commun. 19, 877–908 (2004)

    Article  Google Scholar 

  11. Park H.-W., Kim H.-S.: Motion estimation using low-band-shift method for wavelet-based moving-picture coding. IEEE Trans. Image Process. 9(4), 577–587 (2000)

    Article  Google Scholar 

  12. Röder M., Cardinal J., Hamzaoui R.: Branch and bound algorithms for rate-distortion optimized media streaming. IEEE Trans. Multimed. 8(1), 170–178 (2006)

    Article  Google Scholar 

  13. Sullivan G.J., Wiegand T.: Rate-distortion optimization for video compression. IEEE Signal Process. Mag. 15(6), 74–90 (1998)

    Article  Google Scholar 

  14. Sweldens W.: The lifting scheme: a custom-design construction of biorthogonal wavelets. Appl. Comput. Harmon. Anal. 3(2), 186–200 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  15. Usevitch, B.: Optimal bit allocation for biorthogonal wavelet coding. In: Data Compression Conference, pp. 387–395 (1996)

  16. Usevitch B.: A tutorial on modern lossy wavelet image compression: foundations of JPEG 2000. IEEE Signal Process. Mag. 18(5), 22–34 (2001)

    Article  Google Scholar 

  17. Vetterlli M., Kovacevic J.: Wavelets and Subband Coding. Prentice Hall PTR, Englewood (1995)

    Google Scholar 

  18. Wiegand T., Schwarz H., Joch A., Kossentini F., Sullivan G.J.: Rate-constrained coder control and comparison of video coding standards. IEEE Trans. Circ. Syst. Video Technol. 13(7), 688–703 (2003)

    Article  Google Scholar 

  19. Wiegand T., Sullivan G.J., Bjøntegaard G., Luthra A.: Overview of the H.264/AVC video coding standard. IEEE Trans. Circ. Syst. Video Copress. 13(7), 560–576 (2003)

    Article  Google Scholar 

  20. Wien M.: Variable block-size transforms for H.264/AVC. IEEE Trans. Circ. Syst. Video Technol. 13(7), 604–613 (2003)

    Article  Google Scholar 

  21. Wu Y., Hanke K., Rusert T., Woods J.W.: Enhanced MC-EZBC scalable video coder. IEEE Trans. Circ. Syst. Video Technol. 18(10), 1432–1436 (2008)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guan-Ju Peng.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Peng, GJ., Hwang, WL. & Chen, SJ. AND-OR tree-based mode selection for video coding. SIViP 6, 259–271 (2012). https://doi.org/10.1007/s11760-011-0222-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-011-0222-z

Keywords

Navigation