Adaptive Compression of Stereoscopic Images

  • Alessandro Ortis
  • Francesco Rundo
  • Giuseppe Di Giore
  • Sebastiano Battiato
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8156)


Nowadays the growing availability of stereo cameras for common applications is becoming a commodity. This paper addresses the problem of stereoscopic images data compression proposing an innovative algorithm for compressing Multi Picture Object coded stereopairs. By means of self organizing reconstruction algorithm based on image redundancy we are able to reduce the size of the enclosed JPEG images. The overall perceived (and measured) quality is managed by considering that a stereoscopic image represents the same scene acquired from two different perspectives. In particular we achieve some compression gain just encoding the two images with different quality factors. The reported results and test benchmarks show the robustness and efficiency of the proposed algorithm.


JPEG Compression Stereoscopic Image Normalize Cross Correlation Candidate Block Compression Gain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Anderson, P.: Advanced Display Technologies JISC Technology and Standards Watch. JISC, Bristol (2005)Google Scholar
  2. 2.
    Wikipedia contributors, Polarized 3D system, Wikipedia The Free Encyclopedia (2013),
  3. 3.
    Multi-Picture format, Camera & Imaging Products Association Standardization Committee, CIPA (2009)Google Scholar
  4. 4.
    Wallace, G.K.: The JPEG still picture compression standard. Communications of the ACM 34(4), 30–44 (1991)CrossRefGoogle Scholar
  5. 5.
    Perkins, M.G.: Data compression of stereopairs. IEEE Transactions on Communications 40(4), 684–696 (1992)CrossRefGoogle Scholar
  6. 6.
    Battiato, S., Mancuso, M., Bosco, A., Guarnera, M.: Psychovisual and Statistical Optimization of Quantization Tables for DCT Compression Engines. In: Proceedings of IEEE International Conference on Image Analysis and Processing, pp. 602–606 (2001)Google Scholar
  7. 7.
    Battiato, S., Bosco, C., Bruna, A., Di Blasi, G., Gallo, G.: Statistical Modeling of Huffman Tables Coding. In: Roli, F., Vitulano, S. (eds.) ICIAP 2005. LNCS, vol. 3617, pp. 711–718. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  8. 8.
    Schenkel, M.B., Luo, C., Frossard, P., Wu, F.: Joint decoding of stereo JPEG image Pairs. In: 2010 17th IEEE International Conference on Image Processing (ICIP), pp. 2633–2636 (2010)Google Scholar
  9. 9.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd edn. Prentice Hall, Upper Saddle River (2008)Google Scholar
  10. 10.
    3DMedia – 3D Technology and Software (2013),
  11. 11.
    Pieter, S., Meesters, L., Ijsselsteijn, W.: Perceived quality of compressed stereoscopic images: Effects of symmetric and asymmetric JPEG coding and camera separation. ACM Transactions on Applied Perception (TAP) 3(2), 95–109 (2006)CrossRefGoogle Scholar
  12. 12.
    Briechle, K., Hanebeck, U.D.: Template matching using fast normalized cross correlation. In: International Society for Optics and Photonics, Aerospace/Defense Sensing, Simulation, and Controls, pp. 95–102 (2001)Google Scholar
  13. 13.
    Kohonen, T.: The self-organizing map. Proceedings of the IEEE 78(9), 1464–1480 (1990)CrossRefGoogle Scholar
  14. 14.
    Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing 13(4), 600–612 (2004)CrossRefGoogle Scholar
  15. 15.
    Banitalebi-Dehkordi, A., Pourazad, M.T., Nasiopoulos, P.: A human visual system based 3D video quality metric. In: The 2nd International Conference on 3D Imaging, IC3D, Liege, Belgium (2012)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alessandro Ortis
    • 1
  • Francesco Rundo
    • 2
  • Giuseppe Di Giore
    • 2
  • Sebastiano Battiato
    • 1
  1. 1.Dipartimento di Matematica ed InformaticaUniversità degli Studi di CataniaCataniaItaly
  2. 2.Digital Convergence Group/CSPSTMicroelectronics s.r.l.CataniaItaly

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