Abstract
Although the variable-block-size motion compensation scheme significantly reduces the compensation error, the computational complexity of motion estimation (ME) is tremendously increased at the same time. To reduce the complexity of the variable-block-size ME algorithm, we propose a statistical learning approach to simplify the computation involved in the sub-MB mode selection. Some representative features are extracted during ME with fixed sizes. Then, an off-line pre-classification approach is used to predict the most probable sub-MB modes according to the run-time features. It turns out that only possible sub-MB modes need to perform ME. Experimental results show that the computation complexity is significantly reduced while the video quality degradation and bitrate increment is negligible.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Wu, D., Pan, F., Lim, K.P., Wu, S., Li, Z.G., Lin, X., Rahardja, S., Ko, C.C.: Fast Intermode Decision in H.264/AVC Video Coding. IEEE Trans. Circuits & Systems For Video Technology 15(6), 953–958 (2005)
Kuo, T.-Y., Chan, C.-H.: Fast Variable Block Size Motion Estimation for H.264 Using Likelihood and Correlation of Motion Field. IEEE Trans. Circuits & Systems for Video Technology 16(10), 1185–1195 (2006)
Jain, A.K.: Fundamentals of digital image processing, ch. 4. Prentice-Hall, Englewood Cliffs (1989)
Tourapis, A.M.: Enhanced Predictive Zonal Search for Single and Multiple Frame Motion Estimation. In: SPIE Proceedings of the Visual Comm. Image Proc. (2002)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pan, WH., Chiang, CK., Lai, SH. (2008). Fast Intermode Decision Via Statistical Learning for H.264 Video Coding. In: Satoh, S., Nack, F., Etoh, M. (eds) Advances in Multimedia Modeling. MMM 2008. Lecture Notes in Computer Science, vol 4903. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77409-9_31
Download citation
DOI: https://doi.org/10.1007/978-3-540-77409-9_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77407-5
Online ISBN: 978-3-540-77409-9
eBook Packages: Computer ScienceComputer Science (R0)