Recursively indexed vector quantization of non-stationary sources
Ali Ghanim Al-Araj, Khalid Sayood · 2002
Summary form only given. We present a recursively indexed vector quantizer with the following properties: (1) it is simple to implement with low computational overhead; (2) it is an adaptive algorithm and therefore is well suited for applications where the source is non-stationary; (3) the output rate can easily be changed making it suitable for applications requiring rate control, such as transmission over packet switched networks; and (4) the input vectors can be quantized to within a user specified distortion on a per vector basis rather than on average. We have called the algorithm forward adaptive even though this algorithm also use the past outputs for adaptation. We have tested this algorithm on a number of synthetic hidden Markov sources, and on a video sequence. The results of both tests compare favorably with existing results in the literature.