Wyner-Ziv video coding constitutes an alluring paradigm for visual sensor networks, offering efficient video compression with low complexity encoding characteristics. This work presents a novel hash-driven Wyner-Ziv video coding architecture for visual sensors, implementing the principles of successively refined Wyner-Ziv coding. To this end, so-called side-information refinement levels are constructed for a number of grouped frequency bands of the discrete cosine transform. The proposed codec creates side-information by means of an original overlapped block motion estimation and pixel-based multi-hypothesis prediction technique, specifically built around the pursued refinement strategy. The quality of the side-information generated at every refinement level is successively improved, leading to gradually enhanced Wyner-Ziv coding performance. Additionally, this work explores several temporal prediction structures, including a new hierarchical unidirectional prediction structure, providing both temporal scalability and low delay coding. Experimental results include a thorough evaluation of our novel Wyner-Ziv codec, assessing the impact of the proposed successive refinement scheme and the supported temporal prediction structures for a wide range of hash configurations and group of pictures sizes. The results report significant compression gains with respect to benchmark systems in Wyner-Ziv video coding (e.g., up to 42.03% over DISCOVER) as well as versus alternative state-of-the-art schemes refining the side-information.
Deligiannis, N, Verbist, F, Slowack, J, Van De Walle, R, Schelkens, P & Munteanu, A 2014, 'Progressively refined Wyner-Ziv video coding for visual sensors', ACM Transactions on Sensor Networks, vol. 10, no. 2, 21. <http://dx.doi.org/10.1145/2530279>
Deligiannis, N., Verbist, F., Slowack, J., Van De Walle, R., Schelkens, P., & Munteanu, A. (2014). Progressively refined Wyner-Ziv video coding for visual sensors. ACM Transactions on Sensor Networks, 10(2), Article 21. http://dx.doi.org/10.1145/2530279
@article{1f268a4e23794f339d20ab6488d61d22,
title = "Progressively refined Wyner-Ziv video coding for visual sensors",
abstract = "Wyner-Ziv video coding constitutes an alluring paradigm for visual sensor networks, offering efficient video compression with low complexity encoding characteristics. This work presents a novel hash-driven Wyner-Ziv video coding architecture for visual sensors, implementing the principles of successively refined Wyner-Ziv coding. To this end, so-called side-information refinement levels are constructed for a number of grouped frequency bands of the discrete cosine transform. The proposed codec creates side-information by means of an original overlapped block motion estimation and pixel-based multi-hypothesis prediction technique, specifically built around the pursued refinement strategy. The quality of the side-information generated at every refinement level is successively improved, leading to gradually enhanced Wyner-Ziv coding performance. Additionally, this work explores several temporal prediction structures, including a new hierarchical unidirectional prediction structure, providing both temporal scalability and low delay coding. Experimental results include a thorough evaluation of our novel Wyner-Ziv codec, assessing the impact of the proposed successive refinement scheme and the supported temporal prediction structures for a wide range of hash configurations and group of pictures sizes. The results report significant compression gains with respect to benchmark systems in Wyner-Ziv video coding (e.g., up to 42.03% over DISCOVER) as well as versus alternative state-of-the-art schemes refining the side-information.",
keywords = "Wyner-Ziv coding, hash-driven distributed video coding, low-cost encoding, visual sensors",
author = "Nikolaos Deligiannis and Frederik Verbist and Jurgen Slowack and {Van De Walle}, Rik and Peter Schelkens and Adrian Munteanu",
year = "2014",
month = jan,
language = "English",
volume = "10",
journal = "ACM Transactions on Sensor Networks",
issn = "1550-4859",
publisher = "Association for Computing Machinery (ACM)",
number = "2",
}