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CLC number: TN919.8

On-line Access: 2011-05-09

Received: 2010-06-16

Revision Accepted: 2010-11-19

Crosschecked: 2011-03-31

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Journal of Zhejiang University SCIENCE C 2011 Vol.12 No.5 P.387-396


Distributed video coding with adaptive selection of hash functions

Author(s):  Xin-hao Chen, Lu Yu

Affiliation(s):  Institute of Information and Communication Engineering, Zhejiang University, Hangzhou 310027, China, Zhejiang Provincial Key Laboratory of Information Network Technology, Hangzhou 310027, China

Corresponding email(s):   yul@zju.edu.cn

Key Words:  Hash, Collision, Distributed video coding, Wyner-Ziv

Xin-hao Chen, Lu Yu. Distributed video coding with adaptive selection of hash functions[J]. Journal of Zhejiang University Science C, 2011, 12(5): 387-396.

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%A Xin-hao Chen
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T1 - Distributed video coding with adaptive selection of hash functions
A1 - Xin-hao Chen
A1 - Lu Yu
J0 - Journal of Zhejiang University Science C
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EP - 396
%@ 1869-1951
Y1 - 2011
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1000198

We address the compression efficiency of feedback-free and hash-check distributed video coding, which generates and transmits a hash code of a source information sequence. The hash code helps the decoder perform a motion search. A hash collision is a special case in which the hash codes of wrongly reconstructed information sequences occasionally match the hash code of the source information sequence. This deteriorates the quality of the decoded image greatly. In this paper, the statistics of hash collision are analyzed to help the codec select the optimal trade-off between the probability of hash collision and the length of the hash code, according to the principle of rate-distortion optimization. Furthermore, two novel algorithms are proposed: (1) the nonzero prefix of coefficients (NPC), which indicates the count of nonzero coefficients of each block for the second algorithm, and also saves 8.4% bitrate independently; (2) the adaptive selection of hash functions (AHF), which is based on the NPC and saves a further 2%–6% bitrate on average. The detailed optimization of the parameters of AHF is also presented.

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[1]Aaron, A., Rane, S., Girod, B., 2004. Wyner-Ziv Video Coding with Hash-Based Motion Compensation at the Receiver. Int. Conf. on Image Processing, 5:3097-3100.

[2]Artigas, X., Ascenso, J., Dalai, M., Klomp, S., Kubasov, D., Ouaret, M., 2007. The DISCOVER Codec: Architecture, Techniques and Evaluation. Picture Coding Symp, p.1-4.

[3]Ascenso, J., Pereira, F., 2007. Adaptive Hash-Based Side Information Exploitation for Efficient Wyner-Ziv Video Coding. IEEE Int. Conf. on Image Processing, p.29-32.

[4]Asif, M., Soraghan, J.J., 2008. Wyner Ziv Codec Design for Surveillance System Using Adaptive Puncturing Rate. 3rd Int. Symp. on Communications, Control and Signal Processing, p.1454-1459.

[5]Bjontegaard, G., 2001. Calculation of Average PSNR Differences Between RD-Curves. VCEG 13th Meeting. VCEG-M33.

[6]Brites, C., Pereira, F., 2007. Encoder Rate Control for Transform Domain Wyner-Ziv Video Coding. IEEE Int. Conf. on Image Processing, p.5-8.

[7]Cote, G., Erol, B., Gallant, M., Kossentini, F., 1998. H.263+: video coding at low bit rates. IEEE Trans. Circ. Syst. Video Technol., 8(7):849-866.

[8]Do, T., Shim, H.J., Jeon, B., 2009. Motion Linearity Based Skip Decision for Wyner-Ziv Coding. 2nd IEEE Int. Conf. on Computer Science and Information Technology, p.410-413.

[9]Dufaux, F., Gao, W., Tubaro, S., Vetro, A., 2009. Distributed video coding: trends and perspectives. EURASIP J. Image Video Process., 2009:508167.

[10]Girod, B., Aaron, A.M., Rane, S., Rebollo-Monedero, D., 2005. Distributed video coding. Proc. IEEE, 93(1):71-83.

[11]Guillemot, C., Pereira, F., Torres, L., Ebrahimi, T., Leonardi, R., Ostermann, J., 2007. Distributed monoview and multiview video coding. IEEE Signal Process. Mag., 24(5):67-76.

[12]Guo, M., Lu, Y., Wu, F., Li, S.P., Gao, W., 2007. Distributed Video Coding with Spatial Correlation Exploited Only at the Decoder in Circuits and Systems. IEEE Int. Symp. on Circuits and Systems, p.41-44.

[13]Hua, G., Chen, C.W., 2008. Distributed Video Coding with Zero Motion Skip and Efficient DCT Coefficient Encoding. IEEE Int. Conf. on Multimedia and Expo, p.777-780.

[14]Koopman, P., Chakravarty, T., 2004. Cyclic Redundancy Code (CRC) Polynomial Selection for Embedded Networks. Int. Conf. on Dependable Systems and Networks, p.145-154.

[15]Mukherjee, D., 2009. Parameter selection for Wyner & Ziv coding of Laplacian sources with additive Laplacian or Gaussian innovation. IEEE Trans. Signal Process., 57(8):3208-3225.

[16]Pereira, F., Torres, L., Guillemot, C., Ebrahimi, T., Leonardi, R., Klomp, S., 2008. Distributed video coding: selecting the most promising application scenarios. Signal Process. Image Commun., 23(5):339-352.

[17]Peterson, W.W., Brown, D.T., 1961. Cyclic codes for error detection. Proc. IRE, 49(1):228-235.

[18]Puri, R., Ramchandran, K., 2002. PRISM: a New Robust Video Coding Architecture Based on Distributed Compression Principles. Proc. Annual Allerton Conf. on Communication Control and Computing, 40:586-595.

[19]Puri, R., Ramchandran, K., 2003a. PRISM: a ‘Reversed’ Multimedia Coding Paradigm. Int. Conf. on Image Processing, 1:617-620.

[20]Puri, R., Ramchandran, K., 2003b. PRISM: an Uplink-Friendly Multimedia Coding Paradigm. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, 4:856-859.

[21]Puri, R., Majumdar, A., Ramchandran, K., 2007. PRISM: a video coding paradigm with motion estimation at the decoder. IEEE Trans. Image Process., 16(10):2436-2448.

[22]Slepian, D., Wolf, J., 1973. Noiseless coding of correlated information sources. IEEE Trans. Inform. Theory, 19(4):471-480.

[23]Sullivan, G.J., Wiegand, T., 1998. Rate-distortion optimization for video compression. IEEE Signal Process. Mag., 15:74-90.

[24]Varodayan, D., Aaron, A., Girod, B., 2005. Rate-Adaptive Distributed Source Coding Using Low-Density Parity-Check Codes. Conf. Record of the 39th Asilomar Conf. on Signals, Systems and Computers, p.1203-1207.

[25]Wyner, A., 1975. On source coding with side information at the decoder. IEEE Trans. Inform. Theory, 21(3):294-300.

[26]Wyner, A., Ziv, J., 1976. The rate-distortion function for source coding with side information at the decoder. IEEE Trans. Inform. Theory, 22(1):1-10.

[27]Yang, S.T., Zhao, M.J., Qiu, P.L., 2007. On Wyner-Ziv problem for general sources with average distortion criterion. J. Zhejiang Univ.-Sci. A, 8(8):1263-1270.

[28]Yu, L., Wang, J., 2010. Review of the current and future technologies for video compression. J. Zhejiang Univ.-Sci. C (Comput. & Electron.), 11(1):1-13.

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