Improved Multiple Description Framework Based on Successively Refinable Quantization and Uneven Erasure Protection

A method to produce balanced multiple descriptions (MD) of a source is by successively refinable quantization (SRQ) in conjunction with uneven erasure protection (UEP) (Goyal, 2001; and Tian and Hemami, 2004). This work proposes an improvement to this balanced MD coding framework. In order to generate L descriptions, the set of source samples is first partitioned into L subsets of equal size, then each subset is quantized separately. Further, interleaved systematic Reed Solomon codes of codelength L and decreasing strengths are applied across the streams output by the SRQs. The improvement over the previous UEP-based MD code is evaluated using the expected distortion of the source reconstruction at the decoder as a performance measure. For a Gaussian memory-less source, the asymptotical improvement in performance, as the rate and code block length approach infin, can attain as much as 1.68 dB (for L = 3 and very low probability of description loss), with a tendency to decrease as the number of descriptions and the rate of description loss increase. In the practical setting using scalar SRQ, small rates and small L, the observed improvement generally matches the asymptotical values.