Showing papers by "Chao Tian published in 2004"

Universal multiple description scalar quantization: analysis and design

Abstract: This paper introduces a new high-rate analysis of the multiple description scalar quantizer (MDSQ) with balanced descriptions. The analysis provides insight into the structure of the MDSQ, suggesting the nonoptimality of uniform central quantizer cell lengths, as well as a method to approximate optimal cell lengths. For both level-constrained and entropy-constrained MDSQ, new upper bounds on the granular distortion for sources with smooth probability density functions (pdfs) are derived under the mean-squared error measure, which are 0.4 dB lower than previous results. Based on the insights, a universal multiple description scalar quantizer (UMDSQ) is proposed which, at high rate, can achieve nearly the same performance as the fully optimized entropy-constrained MDSQ (ECMDSQ), without requiring extensive training. The proposed UMDSQ has only two control parameters, and a continuum of tradeoff points between the central and side distortions can be achieved as the two parameters are varied.

An embedded image coding system based on tarp filter with classification

Abstract: Recently, image compression systems based on the tarp filter, a type of recursive filter, have attracted much attention in the image processing community. While providing very good performance when used in a non-embedded manner, the original tarp-filter-based algorithm performs less competitively when used in an embedded manner (in spite of its operation on bitplanes), because of its raster scan encoding order. We propose a Tarp-filter-based system which utilizes Classification of coefficients to achieve Embedding (TCE). The algorithm classifies the coefficients according to their statistical properties, and the tarp filter only runs on the single class on which it tends to generate accurate probability estimates. TCE can achieve much better rate-distortion embedding performance than the original tarp-filter-based system when used in an embedded manner; it achieves slightly better performance than SPIHT with arithmetic coding, and is comparable with JPEG-2000 performance on average.

Sequential design of multiple description scalar quantizers

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.

Optimality and suboptimality of multiple-description vector quantization with a lattice codebook

Abstract: The asymptotic analysis of multiple-description vector quantization (MDVQ) with a lattice codebook for sources with smooth probability density functions (pdfs) is considered in this correspondence. Goyal et al. (2002) observed that as the side distortion decreases and the central distortion correspondingly increases, the quantizer cells farther away from the coarse lattice points shrink in a spatially periodic pattern. In this correspondence, two special classes of index assignments are used along strategic groupings of central quantizer cells to derive a straightforward asymptotic analysis, which provides an analytical explanation for the aforementioned observation. MDVQ with a lattice codebook was shown earlier to be asymptotically optimal in high dimensions, with a curious converging property, that the side quantizers achieve the space filling advantage of an n-dimensional sphere instead of an n-dimensional optimal polytope. The analysis presented here explains this behavior readily. While central quantizer cells on a uniform lattice are asymptotically optimal in high dimensions, the present authors have shown that by using nonuniform rather than uniform central quantizer cells, the central-side distortion product in an MDSQ can be reduced by 0.4 dB at asymptotically high rate. The asymptotic analysis derived here partially unifies these previous results in the same framework, though a complete characterization is still beyond reach.

A special class of multiple description scalar quantizers

Abstract: We introduce a special class of multiple description scalar quantizer (MDSQ), which is referred to as the modified MDSQ (MMDSQ). MMDSQ features simple implementations and an efficient central-side distortion trade-off control mechanism. These advantages make it suitable for multiple description image and video coding systems: the simplicity of MMDSQ facilitates the incorporation of multiple description coding into existing coding systems. Analysis shows that this class of MDSQ can achieve the same asymptotic high-rate performance as entropy-constrained MDSQ with uniform central quantizers, for sources with smooth pdf. The performance of MMDSQ on a unit-variance Gaussian i.i.d. source is compared with that of entropy-constrained MDSQ at different rates numerically, and the results confirm the satisfactory performance of MMDSQ at rates above 3 bps/description. Application of MMDSQ to image coding also shows promising results.