Recursive subband image coding with adaptive prediction and finite state vector quantization

Abstract

This paper discusses a method for subband image coding which employs a number of novel techniques and concepts. Recursive exact reconstruction filters are used for analysis and synthesis to achieve computational savings. Issues related to the filter bank design criteria and the impact of these filters on the subjective quality of decoded images are discussed. A new coding system is introduced which combines the advantages of analysis-by-synthesis, linear prediction and finite state vector quantization to obtain higher compression ratios. This method is used for encoding the lowest frequency subband and is shown to yield improvement over the commonly used methods of differential pulse code modulation and adaptive differential pulse code modulation. A multi-codebook vector quantization strategy is introduced for coding the high frequency subbands which enables inter-band correlation to be exploited. Experimental results and comparisons with previous work are presented which show the utility of this approach.