A conditional enhancement-layer quantizer for the scalable MPEG advanced Audio Coder

Abstract

We propose an efficient enhancement-layer quantizer which considerably improves the bit rate scalability of the multi-layer Advanced Audio Coder (AAC). The scheme exploits the statistical dependence of the enhancement-layer signal on the base-layer quantization parameters. It fundamentally extends the prior work on compander domain scalability, which was shown to be asymptotically optimal for entropy coded uniform scalar quantizer, to systems with non-uniform base-layer quantization. We show that an enhancement-layer quantization which is conditional on the base-layer information can be efficiently implemented within the AAC framework to achieve major performance gains. Moreover, in the important case that the source is well modeled as Laplacian, we show that the optimal conditional quantizer is implementable by only two distinct switchable quantizers depending on whether or not the base-layer quantizer employed the “zero dead-zone.” Hence, major savings in bit rate are recouped at virtually no additional computational cost. For example, the proposed four layer scalable coder consisting of 16kbps layers achieves performance close to a 60kbps non-scalable coder on the standard test database of 44.1kHz audio.