  Most design approaches for trellis-coded quantization take advantage of the
duality of trellis-coded quantization with trellis-coded modulation, and use
the same empirically-found convolutional codes to label the trellis branches.
This letter presents an alternative approach that instead takes advantage of
maximum-Hamming-distance convolutional codes. The proposed source codes are
shown to be competitive with the best in the literature for the same
computational complexity.
