Derailment-free finite state vector quantization using conditional histogram. Optimization and application to image compression

The finite state vector quantization (FSVQ) image compression approach is studied. A new compression scheme is proposed which optimizes the performance of the so-called conditional histogram next-state function design. The optimization is performed by determining for every input block the state codebook size, that minimizes the expected value of the number of bits in the compressed data flow. This is done under the constraint to ensure the same reconstruction quality as that of the full-search vector quantizer. The derailment is avoided by transmitting side information to the decoder. The proposed scheme is tested on still medical endoscopic images. Since the system is always adapted to the probability distribution of block occurrences, it provides a lower bit rate than FSVQ that applies state codebooks of fixed size.