Modern video coding applications require data transmission over variable-bandwidth wired and wireless network channels to a variety of terminals, possibly having different screen resolutions and available computing power. Scalable video coding technology is needed to optimally support these applications. Recently proposed wavelet-based video codecs employing spatial-domain motion-compensated temporal filtering (SDMCTF) provide quality, resolution and frame-rate scalability while delivering compression performance comparable to that of H.264, the state-of-the-art in single-layer video coding. These codecs require quality-scalable coding of the motion vectors to support a large range of bit-rates with optimal compression efficiency. In this paper, the practical use of prediction-based scalable motion vector coding in the context of scalable SDMCTF-based video coding is investigated. Extensive experimental results demonstrate that, irrespective of the employed motion model, our prediction-based scalable motion vector codec (MVC) systematically outperforms state-of-the-art wavelet-based solutions for both lossy and lossless compression. A new rate-distortion optimized rate-allocation strategy is proposed, capable of optimally distributing the available bit-budget between the different frames and between the texture and motion information, making the integration of the scalable MVC into a scalable video codec possible. This rate-allocation scheme systematically outperforms heuristic approaches previously employed in the literature. Experiments confirm that by using a scalable MVC, lower bit-rates can be attained without sacrificing motion-estimation efficiency and that the overall coding performance at low rates is significantly improved by a better distribution of the available rate between texture and motion information. The only downside of scalable motion vector coding is a slight performance loss incurred at high bit-rates.
Barbarien, J, Munteanu, A, Verdicchio, F, Andreopoulos, I, Cornelis, J & Schelkens, P 2005, 'Motion and texture rate-allocation for prediction-based scalable motion-vector coding', Signal Processing: Image Communication, vol. 20, no. 4, pp. 315-342.
Barbarien, J., Munteanu, A., Verdicchio, F., Andreopoulos, I., Cornelis, J., & Schelkens, P. (2005). Motion and texture rate-allocation for prediction-based scalable motion-vector coding. Signal Processing: Image Communication, 20(4), 315-342.
@article{caa67e08d2a742e5ac05f774d3936125,
title = "Motion and texture rate-allocation for prediction-based scalable motion-vector coding",
abstract = "Modern video coding applications require data transmission over variable-bandwidth wired and wireless network channels to a variety of terminals, possibly having different screen resolutions and available computing power. Scalable video coding technology is needed to optimally support these applications. Recently proposed wavelet-based video codecs employing spatial-domain motion-compensated temporal filtering (SDMCTF) provide quality, resolution and frame-rate scalability while delivering compression performance comparable to that of H.264, the state-of-the-art in single-layer video coding. These codecs require quality-scalable coding of the motion vectors to support a large range of bit-rates with optimal compression efficiency. In this paper, the practical use of prediction-based scalable motion vector coding in the context of scalable SDMCTF-based video coding is investigated. Extensive experimental results demonstrate that, irrespective of the employed motion model, our prediction-based scalable motion vector codec (MVC) systematically outperforms state-of-the-art wavelet-based solutions for both lossy and lossless compression. A new rate-distortion optimized rate-allocation strategy is proposed, capable of optimally distributing the available bit-budget between the different frames and between the texture and motion information, making the integration of the scalable MVC into a scalable video codec possible. This rate-allocation scheme systematically outperforms heuristic approaches previously employed in the literature. Experiments confirm that by using a scalable MVC, lower bit-rates can be attained without sacrificing motion-estimation efficiency and that the overall coding performance at low rates is significantly improved by a better distribution of the available rate between texture and motion information. The only downside of scalable motion vector coding is a slight performance loss incurred at high bit-rates.",
keywords = "motion vector coding, scalable video coding, wavelets",
author = "Joeri Barbarien and Adrian Munteanu and Fabio Verdicchio and Ioannis Andreopoulos and Jan Cornelis and Peter Schelkens",
note = "Signal Processing: Image Communication, Vol. 20, Nr. 4, pp. 315-342.",
year = "2005",
month = apr,
language = "English",
volume = "20",
pages = "315--342",
journal = "Signal Processing: Image Communication",
issn = "0923-5965",
publisher = "Elsevier",
number = "4",
}