Robust zero-redundancy vector quantization for noisy channels

The authors present a polynomial-time codeword-mapping algorithm which seeks to minimize the Euclidean distance between all pairs of codewords with a relative Hamming distance of 1, permitting the robust performance of vector quantizations in noisy channels, without a sacrifice in coding bandwidth or quantizer performance. The algorithm is based upon network design considerations, and useful gains of several decibels can be obtained in the error distortion by using the new codeword mapping, without a sacrifice in coding bandwidth or quantizer performance. Results with application to image coding are given, and it is also shown that some natural codes are good robust codes under selected conditions