Joint entropy-scalable coding of audio signals

A fine grain scalable coding for audio signals is proposed where the entropy coding of the quantizer outputs is made scalable. By constructing a Huffman-like coding tree where internal nodes can be mapped to reconstruction points, we can prune the tree to control the distortion of the quantizer. Our results show the proposed method improves existing similar work and significantly outperforms scalable coding based on reconstruction error quantization as used in practical systems, eg. MPEG-4 audio.