Joint source channel coding of images with trellis coded quantization and convolutional codes

The design of a low complexity joint source channel codec for images using trellis coded quantization and convolutional codes is studied. It is shown that a low complexity joint source channel codec offering high robustness is enabled by using the same Ungerboeck trellis code to do both quantization and convolutional coding. Simulation results are presented for joint source channel coding of Gaussian sources over the additive white Gaussian noise channel (AWGN) under the restriction of BPSK modulation; coding of image subband coefficients is also performed. The results compare favorably with those previously reported for systems employing unified trellis source coding and convolutional channel coding, and for pseudo-Gray coded systems. The simulation results also show that there is an optimal allocation of transmission bandwidth between the source and channel codes.