Low-complexity PARCOR coefficient quantization and prediction order estimation designed for entropy coding of prediction residuals

Abstract

This paper presents a set of low-complexity tools used in lossless coding of G.711 bitstream, based on linear prediction. One is an algorithm for quantizing the PARCOR/reflection coefficients and the other is an estimation method for the optimal prediction order. Both tools are based on a criterion that minimizes the entropy of the prediction residual signal and can be implemented in fixed-point arithmetic at very low-complexity. Since proposed methods show efficient performance in terms of compression and complexity, they are adopted in the Recommendation ITU-T G.711.0, a new standard for lossless compression of G.711 (A-law/ -law logarithmic PCM) payload.

Optimal Coding of Generalized-Gaussian-Distributed Frequency Spectra for Low-Delay Audio Coder With Powered All-Pole Spectrum Estimation

“…3(d) might not seem promising for this adaptive use of the since , at least for the test data, already achieves about 103% of bit length compared with the optimal length attainable by tuning. However, this graph is only the result for the 16th-order of PAPSE, so we expect that using PAPSE with adaptive in combination with prediction order estimations, [44], [45] for instance, would increase the efficiency of the compression.…”