Novel VQ with constraints on the quantization error distribution

In this paper, we motivate and introduce a novel vector quantization (VQ) scheme for distributing the quantization error among the quantized features of a continuous feature vector in a predefined manner. This is done by defining ratios between the individual quantization errors of the features and shaping the Voronoi cells accordingly. In a series of experiments we show that the novel approach is capable of either distributing the quantization error equally among the dimensions or realize an arbitrary distribution.