C. Tian

Publications (4)3.01 Total impact

• Source

  Available from: ArXiv

  Article: Multiple Description Quantization Via Gram–Schmidt Orthogonalization

  Jun Chen, Chao Tian, T. Berger, S.S. Hemami
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  ABSTRACT: The multiple description (MD) problem has received considerable attention as a model of information transmission over unreliable channels. A general framework for designing efficient MD quantization schemes is proposed in this paper. We provide a systematic treatment of the El Gamal-Cover (EGC) achievable MD rate-distortion region, and show it can be decomposed into a simplified-EGC (SEGC) region and a superimposed refinement operation. Furthermore, any point in the SEGC region can be achieved via a successive quantization scheme along with quantization splitting. For the quadratic Gaussian case, the proposed scheme has an intrinsic connection with the Gram-Schmidt orthogonalization, which implies that the whole Gaussian MD rate-distortion region is achievable with a sequential dithered lattice-based quantization scheme as the dimension of the (optimal) lattice quantizers becomes large. Moreover, this scheme is shown to be universal for all independent and identically distributed (i.i.d.) smooth sources with performance no worse than that for an i.i.d. Gaussian source with the same variance and asymptotically optimal at high resolution. A class of MD scalar quantizers in the proposed general framework is also constructed and is illustrated geometrically; the performance is analyzed in the high-resolution regime, which exhibits a noticeable improvement over the existing MD scalar quantization schemes
  IEEE Transactions on Information Theory 01/2007; · 3.01 Impact Factor
• Conference Proceeding: Sequential design of multiple description scalar quantizers

  C. Tian, S.S. Hemami
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  ABSTRACT: This paper introduces a new sequential design method for multiple description scalar quantizers (MDSQs) to generate two or more balanced descriptions. In this design method, a multiple description system is divided into multiple stages, and the m-th stage can be understood intuitively as minimizing the distortion of receiving any m of all the descriptions, while looking ahead to the next stage to reduce the distortion if more descriptions are present. Entropy-constrained sequential MDSQ with two descriptions is shown to achieve the same asymptotic performance as entropy-constrained MDSQ with uniform stepsize. Then this method is applied to the design of sequential MDSQ with three descriptions, for which two slightly different designs are given and compared with a three description system based on unequal loss protection at high rate. The results suggest that if the quality of the decoded source with two or more descriptions (rather than a single description) is most important, general multiple description systems should be favored over unequal loss protection systems. However, if the quality of the decoded source with a single description is most important (in the case of, for example, high channel failure rates), the difference in their performances is not terribly large.
  Data Compression Conference, 2004. Proceedings. DCC 2004; 04/2004
• Source

  Available from: psu.edu

  Article: On the asymptotic analysis of multiple description scalar quantization

  C Tian, S S Hemami
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  ABSTRACT: This paper introduces a new asymp-totic analysis of the multiple description scalar quantizer (MDSQ). The analysis provides insight into the structure of the MDSQ, suggesting the non-optimality of uniform central quantizer cells in general. Using the mean-squared error mea-surement, an upper bound of the gap between the distortion product of MDSQ and the multiple de-scription rate distortion bound is found to be 2.67 db for entropy constrained MDSQ (ECMDSQ) for any source with a smooth pdf, and 8.29 dB for level constrained MDSQ with a Gaussian source. These results are 0.4 dB lower than previous re-sults given in [1].
  Conference on Information Sciences and Systems. 04/2003;
• Article: Unknown

  C. Tian, S.S. Hemami
  [show abstract] [hide abstract]
  ABSTRACT: This paper introduces a new asymptotic analysis of the multiple description scalar quantizer (MDSQ). The analysis provides insight into the structure of the MDSQ, suggesting the non-optimality of uniform central quantizer cells in general. Using the mean-squared error measurement, an upper bound of the gap between the distortion product of MDSQ and the multiple description rate distortion bound is found to be 2.67 db for entropy constrained MDSQ (ECMDSQ) for any source with a smooth pdf, and 8.29 dB for level constrained MDSQ with a Gaussian source. These results are 0.4 dB lower than previous results given in [1].
  03/2003;