Multiple Description Lattice Vector Quantization
DCC '99 Proceedings of the Conference on Data Compression
Multiple Description Lattice Vector Quantization: Variations and Extensions
DCC '00 Proceedings of the Conference on Data Compression
Optimal Index Assignment for Multiple Description Lattice Vector Quantization
DCC '06 Proceedings of the Data Compression Conference
Multiple-description vector quantization with lattice codebooks: design and analysis
IEEE Transactions on Information Theory
Asymmetric multiple description lattice vector quantizers
IEEE Transactions on Information Theory
Multiple description vector quantization with a coarse lattice
IEEE Transactions on Information Theory
Fast quantizing and decoding and algorithms for lattice quantizers and codes
IEEE Transactions on Information Theory
Optimality and suboptimality of multiple-description vector quantization with a lattice codebook
IEEE Transactions on Information Theory
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Multiple description lattice vector quantization (MDLVQ) is an effective technique to realize multiple description coding. In this paper, we investigate a 3-description lattice vector quantization (LVQ) design using A"2 lattice, which finds a 3-tuple combination of sublattice points to represent each fine lattice point, based on two principles that each edge of the triangle formed by the 3-tuple points needs to be as short as possible, and the gravity center of the triangle is as close as possible to the fine lattice point. Following a delicate sublattice partition, a well-designed construction and mapping of each fine lattice point to a 3-tuple of sublattice points is developed to minimize the side distortion. The proposed index assignment is shown to achieve smaller distortion (up to 0.58dB for Gaussian source) than some other 3-description index assignments. Compared with a 2-description LVQ, the 3-description LVQ achieves better expected rate-distortion performance in most cases of high description loss rates, while it also exhibits more graceful coding results with significantly smaller side distortions. Numerical analysis on Gaussian source and the simulations on image source validate the effectiveness of our proposed index assignment scheme.