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Progressively refined wyner-ziv video coding for visual sensors

Published: 31 January 2014 Publication History

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 multihypothesis 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.

References

[1]
A. Aaron, S. Rane, and B. Girod. 2004. Wyner-Ziv video coding wioth hash-based motion compensation at the receiver. In Proceedings of the IEEE International Conference on Image Processing (ICIP'04). IEEE, 3097--3100.
[2]
A. Abou-Elailah, F. Dufaux, J. Farah, M. Cagnazzo, and B. Pesquet-Popescu. 2011. Successive refinement of motion compensated interpolation for transform-domain distributed video coding. In Proceedings of the 19th European Signal Processing Conference (EUSIPCO'11)
[3]
A. B. B. Adikari, W. A. C. Fernando, W. A. R. J. Weerakkody, and H. K. Arachchi. 2006. Sequential motion estimation using luminance and chrominance information for distributed video coding of Wyner-Ziv frames. IEE Electron. Lett. 42, 7, 398--399.
[4]
J. J. Ahmad, H. A. Khan, and S. A. Khayam. 2009. Energy efficient video compression for wireless sensor networks. In Proceedings of the Annual Conference on Information Sciences and Systems (CISS'09).
[5]
I. Akyildiz, T. Melodia, and K. Chowdhury. 2007. A survey on wireless multimedia sensor networks. Computer Networks 51, 4, 921--960.
[6]
X. Artigas, J. Ascenso, M. Dalai, S. Klomp, D. Kubasov, and M. Quaret. 2007. The DISCOVER codec: Architecture, techniques and evaluation. In Proceedings of the Picture Coding Symposium (PCS'07).
[7]
X. Artigas and L. Torres. 2005. Iterative generation of motion-compensated side-information for distributed video coding. In Proceedings of the IEEE International Conference on Image Processing (ICIP'05). IEEE, 833--836.
[8]
J. Ascenso, C. Brites, and F. Pereira. 2005. Motion compensated refinement for low complexity pixel based distributed video coding. In Proceedings of the IEEE Conference on Advanced Video Signal Based Surveillance (AVSS'05). 593--598.
[9]
J. Ascenso, C. Brites, and F. Pereira. 2006. Content adaptive Wyner-Ziv video coding driven by motion activity. In Proceedings of the IEEE International Conference on Image Processing (ICIP'06). IEEE, 605--608.
[10]
J. Ascenso, C. Brites, and F. Pereira. 2010. A flexible side information generation framework for distributed video coding. Multimedia Tools Appl. 48, 3, 381--409.
[11]
M. B. Badem, M. Mrak, and W. A. C. Fernando. 2008. Side information refinement using motion estimation in DC domain for transform-based distributed video coding. IEE Electron. Lett. 44, 16, 965--966.
[12]
G. Bjøntegaard. 2001. Calculation of average PSNR differences between RD-curves. ITU-T Video Coding Experts Group (VCEG), Austin, TX.
[13]
M. Camilli and R. Kleihorst. 2011. Demo: Mouse sensor networks, the smart camera. In Proceedings of the ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC'11)
[14]
S. Cheng and Z. Xiong 2005. Successive refinement for the Wyner-Ziv problem and layered code design. IEEE Trans. Signal Process. 53, 8, 3269--3281.
[15]
N. Deligiannis, J. Barbarien, M. Jacobs, A. Munteanu, A. Skodras, and P. Schelkens. 2012a. Side-information dependent correlation channel estimation in hash-based distributed video coding. IEEE Trans. Image Process. 21, 4, 1934--1949.
[16]
N. Deligiannis, M. Jacobs, F. Verbist, J. Slowack, J. Barbarien, R. van de Walle, P. Schelkens, and A. Munteanu. 2011. Efficient hash-driven Wyner-ZIv video coding for visual sensors. In Proceedings of the ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC'11)
[17]
N. Deligiannis, A. Munteanu, T. Clerckx, J. Cornelis, and P. Schelkens. 2009a. Modelling the correlation noise in spatial domain distributed video coding. In Proceedings of the IEEE Data Compression Conference (DCC'09). IEEE, 443.
[18]
N. Deligiannis, A. Munteanu, T. Clerckx, J. Cornelis, and P. Schelkens. 2009b. Overlapped block motion estimation and probabilistic compensation with application in distributed video coding. IEEE Signal Process. Lett. 16, 9, 743--746.
[19]
N. Deligiannis, F. Verbist, A. Iossifides, J. Slowack, R. van de Walle, P. Schelkens, and A. Munteanu. 2012b. Wyner-Ziv video coding for wireless lightweight multimedia applications. EURASIP J. Wirel. Commun. Network.
[20]
N. Deligiannis, F. Verbist, J. Slowack, R. van de Walle, P. Schelkens, and A. Munteanu. 2012c. Joint successive correlation estimation and side information refinement in distributed video coding. In Proceedings of the 20th European Signal Processing Conference (EUSIPCO'12). 569--573.
[21]
C. E. Duchon. 1979. Lanczos filtering in one and two dimensions. J. Appl. Meteorol. 18, 8, 1016--1022.
[22]
X. Fan, O. Au, N. M. Cheung, Y. Chen, and J. Zhou. 2010. Successive refinement based Wyner-Ziv video compression. Signal Process. Image Commun. 25, 47--63.
[23]
B. Girod, A. Aaron, S. Rane, and D. Rebollo-Monedero. 2005. Distributed video coding. Proc. IEEE. 93, 1, 71--83.
[24]
F. Huang and S. Lei. 2008. A high performance and low cost entropy encoder for H.264 AVC baseline entropy coding. In Proceedings of the International Conference on Communications, Circuits and Systems (ICCCAS'08).
[25]
P. Ishwar, V. M. Prabhakaran, and K. Ramchandran. 2003. Towards a theory for video coding using distributed compression principles. In Proceedings of the IEEE International Conference on Image Processing (ICIP'03). IEEE, 687--690.
[26]
D. Kubasov, J. Nayak, and C. Guillemot. 2007. Optimal reconstruction in Wyner-Ziv video coding with multiple side information. In Proceedings of the IEEE Multimedia Signal Processing Workshop (MMSP'07). IEEE, 251--254.
[27]
H.-C. Kuo, L.-C. Wu, H.-T. Huang, S.-T. Hsu, and Y.-L. Lin. 2011. A low-power high-performance H.264/AVC intra-frame encoder for 1080pHD video. IEEE Trans, VLSI Syst. 19, 6, 925--938.
[28]
Z. Li, L. Liu, and E. J. Delp. 2007. Rate distortion analysis of motion side estimation in Wyner-Ziv video coding. IEEE Trans. Image Process. 16, 1, 98--113.
[29]
P. List, A. Joch, J. Lainema, G. Bjøntegaard, and M. Karczewicz. 2003. Adaptive deblocking filter. IEEE Trans. Circuits Syst. Video Technol. 13, 7, 614--619.
[30]
E. Martinian, A. Vetro, J. S. Yedidia, J. Ascenso, A. Khisti, and D. Malioutov. 2006. Hybrid distributed video coding using sca codes. In Proceedings of the IEEE Multimedia Signal Processing Workshop (MMSP'06). IEEE, 258--261.
[31]
R. Martins, C. Brites, J. Ascenso, and F. Pereira. 2009. Refining side information for improved transform domain Wyner-Ziv video coding. IEEE Trans. Circuits Syst. Video Technol. 19, 9, 1327--1341.
[32]
C. McCaffrey, O. Chevalerias, C. O'Mathuna, and K. Twomey. 2008. Swallowable-capsule technology. IEEE Pervasive Comput. 7, 1, 23--29.
[33]
L. Natario, C. Brites, J. Ascenso, and F. Pereira. 2005. Extrapolating side information for low-delay pixel-domain distributed video coding. In Proceedings of the International Workshop on Very Low Bitrate Video Coding (VLVB'05).
[34]
A. V. Oppenheim, R. W. Schafer, and J. R. Buck. 1999. Discrete-Time Signal Processing. Prentice Hall.
[35]
F. Pereira, J. Ascenso, and C. Brites. 2007. Studying the GOP size impact on the performance of a feedback channel based Wyner-Ziv video codec. In Proceedings of the IEEE Pacific Rim Symposium on Image Video and Technology (PSIVT'07).
[36]
R. Puri and K. Ramchandran. 2002. PRISM: A new robust video coding architecture based on distributed compression principles. In Proceedings of the 40th Allerton Conference on Communication, Control, and Computing, 586--595.
[37]
P. Schelkens, A. Skodras, and T. Ebrahimi. 2009. The JPEG 2000 Suite. Wiley.
[38]
D. Slepian and J. K. Wolf. 1973. Noiseless coding of correlated information sources. IEEE Trans. Inf. Theory 19, 4, 471--480.
[39]
Y. Steinberg and N. Merhav. 2004. On successive refinement for the Wyner-Ziv problem. IEEE Trans. Inf. Theory 50, 8, 1636--1654.
[40]
R. Swamy, S. Bates, and T. L. Brandon. 2005. Architectures for ASIC implementations of low-density parity-check convolutional encoders and decoders. In Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS'05).
[41]
D. Taubman and M. W. Marcelin. 2002. JPEG2000: Image Compression Fundamentals, Standards, and Practice. Kluwer Academic Publishers, Norwell, MA.
[42]
Y.-C. Tseng, Y.-C. Wang, K.-Y. Cheng, and Y.-Y. Hsieh. 2007. iMouse: An integrated mobile surveillance and wireless sensor system. IEEE Computer 40, 6, 60--66.
[43]
K. Turkowski and S. Gabriel. 1990. Filters for common resampling tasks. In Graphics Gems I, A. S. Glassner, Ed., Academic Press, San Diego, CA.
[44]
A. Ukhanova, E. Belyaev, and S. Forchhammer. 2010. Encoder power consumption comparison of distributed video codec and H.264/AVC in low complexity mode. In Proceedings of the International Conference on Software, Telecommunications and Computer Networks (SoftCOM'10).
[45]
D. Varodayan, A. Aaron, and B. Girod. 2006. Rate-adaptive codes for distributed source coding. Signal Process. 86, 11, 3123--3130.
[46]
D. Varodayan, D. Chen, M. Flieri, and B. Girod. 2008. Wyner-Ziv coding of video with unsupervised motion vector learning. Signal Process. Image Commun. 23, 5, 369--378.
[47]
F. Verbist, N. Deligiannis, M. Jacobs, J. Barbarien, P. Schelkens, and A. Munteanu. 2011. A statistical approach to create side information in distributed video Coding. In Proceedings of the ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC'11).
[48]
W. Wan, Y. Chen, Y.-K. Wang, M. M. Hannuksela, H. Li, and M. Gabbouj. 2009. Efficient hierarchical inter picture coding for H.264/AVC baseline profile. In Proceedings of the Picture Coding Symposium (PCS'09).
[49]
S. Wang, L Cui., L. Stankovic, V. Stankovic, and S. Cheng. 2012. Adaptive correlation estimation with particle filtering for distributed video coding. IEEE Trans. Circuits Syst. Video Technol. 22, 5, 649--658.
[50]
W. A. R. J. Weerakkody, W. A. C. Fernando, J. L. Martinez, P. Cuenca, and F. Quiles. 2007. An iterative refinement technique for side-information generation in DVC. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME'07). 164--167.
[51]
T. Wiegand, G. J. Sullivan, G. Bjøntegaard, and A. Luthra. 2003. Overview of the H.264/AVC video coding standard. IEEE Trans. Circuits Syst. Video Technol. 13, 7, 560--576.
[52]
A. D. Wyner and J. Ziv. 1976. The rate-distortion function for source coding with side information at the decoder. IEEE Trans. Inf. Theory 22, 1, 1--10.
[53]
Z. Xiong, A. Liveris, and S. Cheng. 2004. Distributed source coding for sensor networks. IEEE Signal Process Mag. 21, 80--94.
[54]
Q. Xu, V. Stankovic, and Z. Xiong. 2007. Distributed joint source-channel coding of video using raptor codes. IEEE J. Sel. Areas Commun. 25, 4, 851--861.
[55]
S. Ye, M. Ouaret, F. Dufaux, and T. Ebrahimi. 2009. Improved side information generation for distributed video coding by exploiting spatial and temporal correlations. EURASIP J. Image Video Process. 1--15.

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cover image ACM Transactions on Sensor Networks
ACM Transactions on Sensor Networks  Volume 10, Issue 2
January 2014
609 pages
ISSN:1550-4859
EISSN:1550-4867
DOI:10.1145/2575808
Issue’s Table of Contents
© 2014 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Publication History

Published: 31 January 2014
Accepted: 01 January 2013
Revised: 01 September 2012
Received: 01 March 2012
Published in TOSN Volume 10, Issue 2

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Author Tags

  1. Wyner-Ziv coding
  2. hash-driven distributed video coding
  3. low-cost encoding
  4. successive refinement
  5. visual sensors

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