On the uniform quantization of a class of sparse sources
IEEE Transactions on Information Theory
Entropy of highly correlated quantized data
IEEE Transactions on Information Theory
A linear encoding approach to index assignment in lossy source-channel coding
IEEE Transactions on Information Theory
Concentric permutation source codes
IEEE Transactions on Communications
| Hi-index | 755.02 |
This correspondence analyzes the low-resolution performance of entropy-constrained scalar quantization. It focuses mostly on Gaussian sources, for which it is shown that for both binary quantizers and infinite-level uniform threshold quantizers, as D approaches the source variance σ2, the least entropy of such quantizers with mean-squared error D or less approaches zero with slope -log2e/2σ2. As the Shannon rate-distortion function approaches zero with the same slope, this shows that in the low-resolution region, scalar quantization with entropy coding is asymptotically as good as any coding technique.