Adaptive vector quantization by progressive codevector replacement

This paper presents a new class of adaptive vector quantizers in which a codebook is gradually changed to track time-varying source statistics by dynamically updating some of the codevectors. The partial distortion of a codevector, defined as the product of the average distortion when a particular codevector is selected and the probability that selection occurs, is used as a measure to determine which codevectors are updated. Codevectors with small partial distortion are deleted from the codebook, and those with large partial distortion are shifted or split so that the input vectors that are mapped into those codevectors are quantized more finely to give smaller partial distortions. Experimental results illustrate the application of this adaptive vector quantizer to image coding.