Abstract
The design of entropy-constrained quantization is formulated as the minimization of quantization error with constraint which gives a maximum amount of information of quantized values. It is known that the optimization of unconstrained quantizer (e.g. a quantizer that minimizes summation of quantization error) is achieved by using approaches based on dynamic programming, which is called DP quantization. However, conventional DP quantization is an approach to optimize a quantizer whose quantization level is fixed. In this paper, we propose a complexity reduction algorithm for an optimal design for entropy-constrained quantizer by extending DP quantization.
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