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Joint bit allocation and dimensions optimization for vector transform quantization

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1 Author(s)
Cuperman, V. ; Sch. of Eng. Sci., Simon Fraser Univ., Burnaby, BC, Canada

In vector transform quantization (VTQ), vectors consisting of M consecutive samples of a waveform are transformed into a set of M coefficients that are quantized by mM vector quantizers. The bit allocation problem in the transform domain is considered for a memoryless stationary vector source encoded by a VTQ system. It is assumed that the vector quantizer parameters (dimension, codebook size) are subject to a complexity constraint. The vector quantization lower bound on the attainable distortion at a given (high) rate is used for deriving the bit allocation algorithm for given vector dimensions. Then, the joint optimization of vector dimensions and bit allocations is considered. Given a complexity constraint, the optimal dimensions depend on the bit allocation, which, in turn, depends on the dimensions. An iterative algorithm is proposed for solving this problem

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Information Theory, IEEE Transactions on  (Volume:39 ,  Issue: 1 )