Multiple-Description Coding by Dithered Delta–Sigma Quantization

We address the connection between the multiple-description (MD) problem and delta-sigma quantization. The inherent redundancy due to oversampling in delta-sigma quantization, and the simple linear-additive noise model resulting from dithered lattice quantization, allow us to construct a symmetric and time-invariant MD coding scheme. We show that the use of a noise-shaping filter makes it possible to trade off central distortion for side distortion. Asymptotically, as the dimension of the lattice vector quantizer and order of the noise-shaping filter approach infinity, the entropy rate of the dithered delta-sigma quantization scheme approaches the symmetric two-channel MD rate-distortion function for a memoryless Gaussian source and mean square error (MSE) fidelity criterion, at any side-to-central distortion ratio and any resolution. In the optimal scheme, the infinite-order noise-shaping filter must be minimum phase and have a piecewise flat power spectrum with a single jump discontinuity. An important advantage of the proposed design is that it is symmetric in rate and distortion by construction, so the coding rates of the descriptions are identical and there is therefore no need for source splitting.

[1]  Allen Gersho,et al.  Asymptotically optimal block quantization , 1979, IEEE Trans. Inf. Theory.

[2]  Jan Ostergaard,et al.  Multiple-Description Lattice Vector Quantization , 2007, 0707.2482.

[3]  Toby Berger,et al.  Successive Coding in Multiuser Information Theory , 2007, IEEE Transactions on Information Theory.

[4]  Vivek K Goyal,et al.  Multiple description transform coding: robustness to erasures using tight frame expansions , 1998, Proceedings. 1998 IEEE International Symposium on Information Theory (Cat. No.98CH36252).

[5]  Ram Zamir,et al.  Dithered lattice-based quantizers for multiple descriptions , 2002, IEEE Trans. Inf. Theory.

[6]  Shlomo Shamai,et al.  Nested linear/Lattice codes for structured multiterminal binning , 2002, IEEE Trans. Inf. Theory.

[7]  Kannan Ramchandran,et al.  n-channel symmetric multiple descriptions-part II:An achievable rate-distortion region , 2005, IEEE Transactions on Information Theory.

[8]  J. Massey CAUSALITY, FEEDBACK AND DIRECTED INFORMATION , 1990 .

[9]  Steven Kay,et al.  Modern Spectral Estimation: Theory and Application , 1988 .

[10]  Kannan Ramchandran,et al.  Generalized coset codes for distributed binning , 2005, IEEE Transactions on Information Theory.

[11]  N. J. A. Sloane,et al.  Design of asymmetric multiple description lattice vector quantizers , 2000, Proceedings DCC 2000. Data Compression Conference.

[12]  Yuval Kochman,et al.  Noise-Shaped Predictive Coding for Multiple Descriptions of a Colored Gaussian Source , 2008, Data Compression Conference (dcc 2008).

[13]  Vivek K. Goyal,et al.  Multiple description coding with many channels , 2003, IEEE Trans. Inf. Theory.

[14]  Abbas El Gamal,et al.  Achievable rates for multiple descriptions , 1982, IEEE Trans. Inf. Theory.

[15]  T.H. Crystal,et al.  Linear prediction of speech , 1977, Proceedings of the IEEE.

[16]  Martin Vetterli,et al.  Wavelets, approximation, and compression , 2001, IEEE Signal Process. Mag..

[17]  Vivek K Goyal,et al.  Quantized Frame Expansions with Erasures , 2001 .

[18]  Albert Wang,et al.  Multiple description decoding of overcomplete expansions using projections onto convex sets , 1999, Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096).

[19]  S. Shamai,et al.  Nested linear/lattice codes for Wyner-Ziv encoding , 1998, 1998 Information Theory Workshop (Cat. No.98EX131).

[20]  Vivek K. Goyal,et al.  Quantized frame expansions as source-channel codes for erasure channels , 1999, Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096).

[21]  Vivek K. Goyal,et al.  Filter bank frame expansions with erasures , 2002, IEEE Trans. Inf. Theory.

[22]  Chao Tian,et al.  A new class of universal multiple description lattice quantizers , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[23]  S. Tewksbury,et al.  Oversampled, linear predictive and noise-shaping coders of order N g 1 , 1978 .

[24]  J. Makhoul,et al.  Linear prediction: A tutorial review , 1975, Proceedings of the IEEE.

[25]  Vivek K. Goyal,et al.  Quantized oversampled filter banks with erasures , 2001, Proceedings DCC 2001. Data Compression Conference.

[26]  R. P. Marques,et al.  Discrete-Time Markov Jump Linear Systems , 2004, IEEE Transactions on Automatic Control.

[27]  Frank Stenger,et al.  Whittaker's Cardinal Function in Retrospect* , 1971 .

[28]  Gabor C. Temes,et al.  Oversampling delta-sigma data converters : theory, design, and simulation , 1992 .

[29]  Kannan Ramchandran,et al.  -Channel Symmetric Multiple Descriptions—Part I: , 2004 .

[30]  N. J. A. Sloane,et al.  Multiple-description vector quantization with lattice codebooks: Design and analysis , 2001, IEEE Trans. Inf. Theory.

[31]  Alan V. Oppenheim,et al.  Compensation of Coefficient Erasures in Frame Representations , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[32]  Vinay A. Vaishampayan,et al.  Design of multiple description scalar quantizers , 1993, IEEE Trans. Inf. Theory.

[33]  N. J. A. Sloane,et al.  Asymmetric multiple description lattice vector quantizers , 2002, IEEE Trans. Inf. Theory.

[34]  Gabor C. Temes,et al.  Oversampled, Linear Predictive and NoiseShaping Coders of Order N , 1992 .

[35]  Jesper Jensen,et al.  Source-Channel Erasure Codes with Lattice Codebooks for Multiple Description Coding , 2006, 2006 IEEE International Symposium on Information Theory.

[36]  A. W. M. van den Enden,et al.  Discrete Time Signal Processing , 1989 .

[37]  Thomas C. Hales Sphere packings, I , 1997, Discret. Comput. Geom..

[38]  Meir Feder,et al.  On lattice quantization noise , 1996, IEEE Trans. Inf. Theory.

[39]  L. Ozarow,et al.  On a source-coding problem with two channels and three receivers , 1980, The Bell System Technical Journal.

[40]  Ram Zamir Gaussian codes and Shannon bounds for multiple descriptions , 1999, IEEE Trans. Inf. Theory.

[41]  N. Jayant Subsampling of a DPCM speech channel to provide two “self-contained” half-rate channels , 1981, The Bell System Technical Journal.

[42]  Helmut Bölcskei,et al.  Noise reduction in oversampled filter banks using predictive quantization , 2001, IEEE Trans. Inf. Theory.

[43]  Chao Tian,et al.  Multiple Description Quantization Via Gram–Schmidt Orthogonalization , 2005, IEEE Transactions on Information Theory.

[44]  Kannan Ramchandran,et al.  n-channel symmetric multiple descriptions - part I: (n, k) source-channel erasure codes , 2004, IEEE Transactions on Information Theory.

[45]  W. Fischer,et al.  Sphere Packings, Lattices and Groups , 1990 .

[46]  A. Calderbank,et al.  On reducing granular distortion in multiple description quantization , 1998, Proceedings. 1998 IEEE International Symposium on Information Theory (Cat. No.98CH36252).

[47]  Alan V. Oppenheim,et al.  Quantization Noise Shaping on Arbitrary Frame Expansions , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[48]  G. Bachman,et al.  Fourier and Wavelet Analysis , 2002 .

[49]  Meir Feder,et al.  Information rates of pre/post-filtered dithered quantizers , 1993, IEEE Trans. Inf. Theory.

[50]  Yuval Kochman,et al.  Achieving the Gaussian Rate–Distortion Function by Prediction , 2007, IEEE Transactions on Information Theory.

[51]  David L. Neuhoff,et al.  Quantization , 2022, IEEE Trans. Inf. Theory.

[52]  Jesper Jensen,et al.  n-channel asymmetric multiple-description lattice vector quantization , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[53]  Jesper Jensen,et al.  n-channel entropy-constrained multiple-description lattice vector quantization , 2006, IEEE Transactions on Information Theory.

[54]  Meir Feder,et al.  On universal quantization by randomized uniform/lattice quantizers , 1992, IEEE Trans. Inf. Theory.