On the Rate-Distortion Function for Binary Source Coding With Side Information

We present an in-depth analysis of the problem of lossy compression of binary sources in the presence of correlated side information, where the correlation is given by a generic binary asymmetric channel and the Hamming distance is the distortion metric. Our analysis is motivated by systematic rate-distortion gains observed when applying asymmetric correlation models in Wyner-Ziv video coding. First, we derive for the first time the rate-distortion function for conventional predictive coding in the binary-asymmetric-correlation-channel scenario. Second, we propose a new bound for the case where the side information is only available at the decoder-Wyner-Ziv coding. We conjecture this bound to be tight. We show that the maximum rate needed to encode as well as the maximum rate-loss of Wyner-Ziv coding relative to predictive coding corresponds to uniform sources and symmetric correlations. Importantly, we show that the upper bound on the rate-loss established by Zamir is not tight and that the maximum value is actually significantly lower. Moreover, we prove that the only binary correlation channel that incurs no rate-loss for Wyner-Ziv coding compared with predictive coding is the Z-channel. Finally, we complement our analysis with new compression performance results obtained with our state-of-the-art Wyner-Ziv video coding system.

[1]  Catarina Brites,et al.  Correlation Noise Modeling for Efficient Pixel and Transform Domain Wyner–Ziv Video Coding , 2008, IEEE Transactions on Circuits and Systems for Video Technology.

[2]  Aaron D. Wyner,et al.  The rate-distortion function for source coding with side information at the decoder , 1976, IEEE Trans. Inf. Theory.

[3]  Margreta Kuijper,et al.  Distributed Source Coding via Linear Block Codes: A General Framework for Multiple Sources , 2012, IEEE Transactions on Communications.

[4]  Bernd Girod,et al.  Compression with side information using turbo codes , 2002, Proceedings DCC 2002. Data Compression Conference.

[5]  Bernd Girod,et al.  Rate-adaptive codes for distributed source coding , 2006, Signal Process..

[6]  Andrei-Tudor Sechelea Binary Source Coding with Side-Information , 2016 .

[7]  Zixiang Xiong,et al.  Successive refinement for the Wyner-Ziv problem and layered code design , 2005, IEEE Trans. Signal Process..

[8]  Michael Gastpar,et al.  To code, or not to code: lossy source-channel communication revisited , 2003, IEEE Trans. Inf. Theory.

[9]  Rik Van de Walle,et al.  Progressively refined wyner-ziv video coding for visual sensors , 2014, TOSN.

[10]  Zixiang Xiong,et al.  Computing the channel capacity and rate-distortion function with two-sided state information , 2005, IEEE Transactions on Information Theory.

[11]  Peter Schelkens,et al.  Overlapped Block Motion Estimation and Probabilistic Compensation with Application in Distributed Video Coding , 2009, IEEE Signal Processing Letters.

[12]  Samuel Cheng,et al.  The No-Rate-Loss Property of Wyner-Ziv Coding in the Z-Channel Correlation Case , 2014, IEEE Communications Letters.

[13]  Robert J. McEliece,et al.  The Constantin-Rao Construction for Binary Assymmetric Error-Correcting Codes , 1980, Inf. Control..

[14]  Søren Forchhammer,et al.  Re-estimation of Motion and Reconstruction for Distributed Video Coding , 2014, IEEE Transactions on Image Processing.

[15]  Aaron D. Wyner,et al.  The rate-distortion function for source coding with side information at the decoder , 1976, IEEE Trans. Inf. Theory.

[16]  Thomas Maugey,et al.  Key view selection in distributed multiview coding , 2014, 2014 IEEE Visual Communications and Image Processing Conference.

[17]  Oscar C. Au,et al.  Transform-Domain Adaptive Correlation Estimation (TRACE) for Wyner–Ziv Video Coding , 2010, IEEE Transactions on Circuits and Systems for Video Technology.

[18]  João Ascenso,et al.  HEVC backward compatible scalability: A low encoding complexity distributed video coding based approach , 2015, Signal Process. Image Commun..

[19]  Bernd Girod,et al.  Distributed Video Coding , 2005, Proceedings of the IEEE.

[20]  Peter Schelkens,et al.  Joint DC coefficient band decoding and motion estimation in Wyner-Ziv video coding , 2011, 2011 17th International Conference on Digital Signal Processing (DSP).

[21]  Samuel Cheng,et al.  Binary rate distortion with side information: The asymmetric correlation channel case , 2015, 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

[22]  Athanassios N. Skodras,et al.  Side-Information-Dependent Correlation Channel Estimation in Hash-Based Distributed Video Coding , 2012, IEEE Transactions on Image Processing.

[23]  Richard E. Blahut,et al.  Computation of channel capacity and rate-distortion functions , 1972, IEEE Trans. Inf. Theory.

[24]  Ram Zamir,et al.  The rate loss in the Wyner-Ziv problem , 1996, IEEE Trans. Inf. Theory.

[25]  Xin Huang,et al.  Cross-band noise model refinement for transform domain Wyner-Ziv video coding , 2012, Signal Process. Image Commun..

[26]  Aaron D. Wyner,et al.  Recent results in the Shannon theory , 1974, IEEE Trans. Inf. Theory.

[27]  Rik Van de Walle,et al.  Distributed coding of endoscopic video , 2011, 2011 18th IEEE International Conference on Image Processing.

[28]  Tracey Ho,et al.  On Source Coding with Coded Side Information for a Binary Source with Binary Side Information , 2007, 2007 IEEE International Symposium on Information Theory.

[29]  Reginald L. Lagendijk,et al.  The role of the virtual channel in distributed source coding of video , 2005, IEEE International Conference on Image Processing 2005.

[30]  Peter Schelkens,et al.  Modeling the Correlation Noise in Spatial Domain Distributed Video Coding , 2009, 2009 Data Compression Conference.

[31]  Aaron D. Wyner,et al.  On source coding with side information at the decoder , 1975, IEEE Trans. Inf. Theory.

[32]  Peter Schelkens,et al.  Transform-domain Wyner-Ziv video coding for 1K-pixel visual sensors , 2013, 2013 Seventh International Conference on Distributed Smart Cameras (ICDSC).

[33]  T. R. N. Rao,et al.  Concatenated group theoretic codes for binary asymmetric channels , 1977, AFIPS '77.

[34]  Aleksandra Pizurica,et al.  Achievability of the rate-distortion function in binary uniform source coding with side information , 2016, 2016 23rd International Conference on Telecommunications (ICT).

[35]  Cong Ling,et al.  Wyner-Ziv Coding Based on Multidimensional Nested Lattices , 2012, IEEE Transactions on Communications.

[36]  R. A. McDonald,et al.  Noiseless Coding of Correlated Information Sources , 1973 .

[37]  Yossef Steinberg,et al.  Coding and Common Reconstruction , 2009, IEEE Transactions on Information Theory.

[38]  Peter Schelkens,et al.  On the side-information dependency of the temporal correlation in Wyner-Ziv video coding , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[39]  Ajay Luthra,et al.  Overview of the H.264/AVC video coding standard , 2003, IEEE Trans. Circuits Syst. Video Technol..

[40]  Marco Dalai,et al.  The DISCOVER codec: Architecture, Techniques and Evaluation , 2007, PCS 2007.

[41]  Aline Roumy,et al.  Source Coding with Side Information at the Decoder and Uncertain Knowledge of the Correlation , 2014, IEEE Transactions on Communications.

[42]  T. Berger Rate-Distortion Theory , 2003 .

[43]  Thomas Maugey,et al.  Depth-Based Multiview Distributed Video Coding , 2014, IEEE Transactions on Multimedia.

[44]  Rik Van de Walle,et al.  Wyner-Ziv video coding for wireless lightweight multimedia applications , 2012, EURASIP J. Wirel. Commun. Netw..