Joint optimization of multi-dimensional SOFM codebooks with QAM modulations for vector quantized image transmission

Abstract

The requirements of digital transmission systems are now becoming so severe that it is no longer possible to optimize different functions in the system independently. Powerful source coding techniques are used to increase the number of sources transmitted in a given frequency bandwidth. However, the quality of the transmitted sources using these source coding techniques usually depends on the channel bit error rate. To go one step further, one would expect the subjective quality of the transmitted sources to remain acceptable even at a very low channel signal to noise ratio as in an analogue transmission system. Traditionally, source coding and channel modulation characteristics are optimized separately. Source coding reduces the redundancy in an input signal, while the modulation adapts the information to the transmission channel characteristics to be noise resistant. In this chapter, the internal structure of the source coding scheme is trained in conjunction with a QAM modulation type to increase the tolerance of transmission error effects. Results obtained using the standard Lenna images are extremely encouraging.