Advertisement

Image and Video Acquisition, Representation and Storage

  • Francesco CamastraEmail author
  • Alessandro Vinciarelli
Chapter
Part of the Advanced Information and Knowledge Processing book series (AI&KP)

Abstract

What the reader should know to understand this chapter \(\bullet \) Elementary notions of optics and physics. \(\bullet \) Basic notions of mathematics.

Keywords

Discrete Cosine Transform Color Space Color Model Discrete Cosine Transform Coefficient Video Object 
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.

References

  1. 1.
    T. Acharaya and A. K. Ray. Image Processing: Principles and Applications. John Wiley and Sons, 2005.Google Scholar
  2. 2.
    F.L. Alt. Digital pattern recognition by moments. Journal of ACM, 11:240–258, 1962.Google Scholar
  3. 3.
    D. Ballard and C. Brown. Computer Vision. Academic Press, 1982.Google Scholar
  4. 4.
    B. E. Bayer. Color imaging array. Color us patent 3,971,065. Technical report, Eastman Kodak Company, 1976.Google Scholar
  5. 5.
    K. M. Bhurchandi, A. K. Ray, and P. M. Nawghare. An analytical approach for sampling the rgb color space considering physiological limitations of human vision and its application for color image analysis. In Proceedings of Indian Conference on Computer Vision, Graphics and Image Processing, pages 44–49, 2000.Google Scholar
  6. 6.
    J. Bormans, J. Gelissen, and A. Perkis. Mpeg-21: The 21\(^{st}\) century multimedia framework. IEEE Signal Processing Magazine, pages 53–62, 2003.Google Scholar
  7. 7.
    G. Buchsbaum. An analytical derivation of visual nonlinearity. IEEE Transactions on biomedical engineering, BME-27(5):237–242, 1980.Google Scholar
  8. 8.
    C. K. Chui. An Introduction to Wavelets. Academic Press, 1982.Google Scholar
  9. 9.
    T. H. Cormen, C. E. Leiserson, and R. L. Rivest. Introduction to Algorithms. MIT Press, 1990.Google Scholar
  10. 10.
    I. Daubechies. Ten Lectures on Wavelets. SIAM, 1992.Google Scholar
  11. 11.
    A. Del Bimbo. Visual Information Retrieval. Morgan Kaufman Publishers, 1999.Google Scholar
  12. 12.
    T. Ebrahimi. Mpeg-4 video verification model: A video encoding/decoding algorithm based on content representation. Image Communication Journal, 9(4):367–384, 1996.Google Scholar
  13. 13.
    K. S. Gibson and D. Nickerson. Analysis of the Munsell colour system based on measurements made in 1919 and 1926. Journal of Optical Society of America, 3(12):591–608, 1940.Google Scholar
  14. 14.
    R. C. Gonzalez and R. E. Woods. Digital Image Processing. Addison Wesley, 1992.Google Scholar
  15. 15.
    G. Healey and Q. Luong. Color in computer vision: Recent progress. In Handbook of Pattern Recognition and Computer Vision, pages 283–312. World Scientific Publishing, 1998.Google Scholar
  16. 16.
    M. K. Hu. Visual pattern recognition by moment invariants. IRE Transactions on Information Theory, 8:351–364, 1962.Google Scholar
  17. 17.
    D. A. Huffman. A method for the construction of minimum-redundancy codes. Proceedings of the IRE, 40(9):1098–1101, 1952.Google Scholar
  18. 18.
    L. M. Hurvich and D. Jameson. An opponent process theory of colour vision. Psychological Review, 64(6):384–404, 1957.Google Scholar
  19. 19.
    L. M. Hurvich and D. Jameson. Some quantitative aspects of an opponent-colors theory: IV A psychological color specification system. Journal of the Optical Society of America, 45(6):416–421, 1957.Google Scholar
  20. 20.
    A. K. Jain. Fundamentals of Digital Image Processing. Prentice-Hall, 1989.Google Scholar
  21. 21.
    D. B. Judd and G. Wyszecki. Color in Business, Science and Industry. John Wiley and Sons, 1975.Google Scholar
  22. 22.
    H. R. Kang. Color Technology for Electronic Imaging Devices. SPIE Optical Engineering Press, 1997.Google Scholar
  23. 23.
    R. Koenen, F. Pereira, and L. Chiariglione. Mpeg-4: Context and objectives. Image Communication Journal, 9(4):295–304, 1997.Google Scholar
  24. 24.
    E. H. Land. Color vision and the natural images. Proceedings of the National Academy of Sciences, 45(1):116–129, 1959.Google Scholar
  25. 25.
    D. Le Gall. Mpeg: a video compression standard for multimedia applications. Communications of the ACM, 34(4):46–58, 1991.Google Scholar
  26. 26.
    D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91–110, 2004.Google Scholar
  27. 27.
    S. Mallat. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(7):674–693, 1998.Google Scholar
  28. 28.
    G. W. Meyer. Tutorial on colour science. The Visual Computer, 2(5):278–290, 1986.Google Scholar
  29. 29.
    M. Miyahara and Y. Yoshida. Mathematical transform of rgb colour data to munsell colour system. In SPIE Visual Communication and Image Processing ’88, pages 650–657, 1988.Google Scholar
  30. 30.
    A. H. Munsell. An Atlas of the Munsell System. Wassworth-Howland, 1915.Google Scholar
  31. 31.
    C. L. Novak and S. A. Shafer. Color Vision. Encyclopedia of Artificial Intelligence. John Wiley and Sons, 1992.Google Scholar
  32. 32.
    W. B. Pennebaker and J. L. Mitchell. JPEG Still Image Data Compression Standard. Chapman & Hall, 1993.Google Scholar
  33. 33.
    W. K. Pratt. Digital Image Processing. John Wiley and Sons, 1991.Google Scholar
  34. 34.
    K. R. Rao and P. Yip. Digital Cosine Transform: Algorithms, Advantages, Applications. Academic Press, 1990.Google Scholar
  35. 35.
    T. Sakamoto, C. Nakanishi, and T. Hase. Software pixel interpolation for digital still cameras suitable for a 32-bit mcu. IEEE Transactions on Consumer Electronics, 44(4):1342–1352, 1998.Google Scholar
  36. 36.
    P. Salembier and J. R. Smith. Mpeg-7 multimedia description schemes. IEEE Transactions on Circuits and Systems for Video Technology, 11(6):748–759, 2001.Google Scholar
  37. 37.
    G. Sharma. Digital color imaging. IEEE Transactions on Image Processing, 6(7):901–932, 1997.Google Scholar
  38. 38.
    A. S. Tanenbaum. Modern Operating Systems. Prentice-Hall, 2001.Google Scholar
  39. 39.
    E. Trucco and A. Verri. Introductory Techniques for 3-D Computer Vision. Prentice-Hall, 1998.Google Scholar
  40. 40.
    P. Tsai, T. Acharaya, and A. K. Ray. Adaptive fuzzy color interpolation. Journal of Electronic Imaging, 11(3):293–305, 2002.Google Scholar
  41. 41.
    B. A. Wandell. Foundations of Vision. Sinauer Associates, 1995.Google Scholar
  42. 42.
    G. Wyszecki and W. S. Stiles. Color Science. Mc Graw-Hill, 1982.Google Scholar

Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  1. 1.Department of Science and TechnologyParthenope University of NaplesNaplesItaly
  2. 2.School of Computing Science and the Institute of Neuroscience and PsychologyUniversity of GlasgowGlasgowUK

Personalised recommendations