Image coding using fuzzy vector quantizer
The fuzzy vector quantizer (FVQ) technique is applied to image coding when a square image subblock is mapped into a reproduction codeword. The FVQ is also tested on a database of Gauss Markov sources to demonstrate its performance in coding highly correlated data. An attempt is made to determine whether the use of softer decisions in the FVQ training step would optimize the codeword distribution and make the quantizer adapt well to random initial codebooks. The experiments show that FVQ coding performs better than standard methods.<<ETX>>