We propose a new approach to achieve eÆcient scalability in audio coders, and demonstrate its performance using the MPEG-4 Advanced Audio Coder (AAC). In conventional scalable coding, the enhancement-layer performs straightforward re-quantization of the base-layer reconstruction error. This coding scheme implicitly discards useful information from the base-layer, and does not truly minimize a perceptually meaningful distortion criterion such as the noise-mask ratio. We reformulate the problem of scalable coding within a companding framework, and show that re-quantization in the compander's compressed domain achieves, in the asymptotic sense, optimal scalability. Based on this observation, we develop a scalable AAC coder which performs enhancement-layer quantization while exploiting all the information available at that layer. Simulation results of a two-layer scalable coder on the standard test database of 44.1kHz sampled audio show that the proposed approach yields substantial savings in bit rate for a given reproduction quality.
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