Abstract
Scalable video coding provides an efficient solution when video is delivered through heterogeneous networks to terminals with different computational and display capabilities. Scalable video bitstream can easily be adapted to required spatio-temporal resolution and quality, according to the transmission requirements. In this chapter, the Wavelet-based Scalable Video Coding (W-SVC) architecture is presented in detail. The W-SVC framework is based on wavelet based motion compensated approaches. The practical capabilities of the W-SVC are also demonstrated by using the error resilient transmission and surveillance applications. The experimental result shows that the W-SVC framework produces improved performance than existing method and provides full flexible architecture with respect to different application scenarios.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Mrak, M., Sprljan, N., Zgaljic, T., Ramzan, N., Wan, S., Izquierdo, E.: Performance evidence of software proposal for Wavelet Video Coding Exploration group. In: 76th MPEG Meeting ISO/IEC JTC1/SC29/WG11/ MPEG2006/M13146, Montreux, Switzerland (April 2006)
Ohm, J.-R.: Three-dimensional Subband Coding with Motion Compensation. IEEE Trans. Image Processing 3, 559–571 (1994)
Sweldens, W., Schroder, P.: Building your own wavelets at home. Wavelets in Computer Graphics, ACM SIGGRAPH Course notes, 15–87 (1996)
Zgaljic, T., Sprljan, N., Izquierdo, E.: Bitstream syntax description based adaptation of scalable video. In: Integration of Knowledge, Semantics and Digital Media Technology (EWIMT 2005), November 30, pp. 173–176 (2005)
Adami, N., Signoroni, A., Leonardi, R.: State-of-the-Art and Trends in Scalable Video Compression With Wavelet-Based Approaches. IEEE Transc. on Circuits and Systems for Video Technology 17(9) (September 2007)
Taubman, D.: High performance scalable image compression with EBCOT. IEEE Trans. Image Processing 9, 1158–1170 (2000)
Kondi, L.P., Ishtiaq, F., Katsaggelos, A.K.: Joint source-channel coding for motion-compensated DCT-based SNR scalable video. IEEE Trans. Image Process. 11(9), 1043–1052 (2002)
Ramzan, N., Wan, S., Izquierdo, E.: Joint Source-Channel Coding for Wavelet Based Scalable Video Transmission using an Adaptive Turbo Code. EURASIP Journal on Image and Video Processing, Article ID 47517, 12 pages (2007)
Zgaljic, T., Ramzan, N., Akram, M., Izquierdo, E., Caballero, R., Finn, A., Wang, H., Xiong, Z.: Surveillance Centric Coding. In: Proc. Of 5th International Conf. on Visual Information Engineering, VIE (July 2008)
Kim, J., Mersereau, R.M., Altunbasak, Y.: Error-resilient image and video transmission over the Internet using unequal error protection. IEEE Trans. Image Process. 12(2), 121–131 (2003)
Thomos, N., Boulgouris, N.V., Strintzis, M.G.: Wireless image transmission using turbo codes and optimal unequal error protection. IEEE Trans. Image Process. 14(11), 1890–1901 (2005)
Banister, B.A., Belzer, B., Fischer, T.R.: Robust video transmission over binary symmetric channels with packet erasures. In: Proc. Data Compression Conference, DCC 2002, pp. 162–171 (2002)
Berrou, C., Glavieux, A.: Near-optimum error-correction coding and decoding: Turbo codes. IEEE Trans. Commun. 44(10), 1261–1271 (1996)
Doulliard, C., Berrou, C.: Turbo codes with rate-m/(m+1) constituent convolutional codes. IEEE Trans. Commun. 53(10), 1630–1638 (2005)
Stauffer, C., Grimson, W.E.L.: Learning patterns of activity using real-time tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 747–757 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Ramzan, N., Izquierdo, E. (2011). Scalable Video Coding and Its Applications. In: Lin, W., Tao, D., Kacprzyk, J., Li, Z., Izquierdo, E., Wang, H. (eds) Multimedia Analysis, Processing and Communications. Studies in Computational Intelligence, vol 346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19551-8_20
Download citation
DOI: https://doi.org/10.1007/978-3-642-19551-8_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19550-1
Online ISBN: 978-3-642-19551-8
eBook Packages: EngineeringEngineering (R0)