Abstract

This paper proposes an efficient, rate-scalable, low complexity audio coder based on the SPIHT (set partitioning in hierarchical trees) coding algorithm [5], which has achieved notable success in still image coding. A wavelet packet transform is used to decompose the audio signal into 29 frequency subbands corresponding roughly to the critical subbands of the human auditory system. A psychoacustic model,which, for simplicity, is based on MPEG model I, is used to calculate the signal to mask ratio, and then calculate the bit rate allocation among subbands. We distinguish the subbands into two groups: the low frequency group whichcontains the rst 17 subbands corresponding to 0-3.4 KHz, and the high frequency group which contains the remaining high frequency subbands. The SPIHT algorithm is used to encoder and decode the low frequency group and a reverse sorting process plus arithmetic coding algorithm is used to encode and decode the high frequency group. The experiment shows that this coder yields nearly transparent quality at bit rates 55-66 Kbits/second, and and degrades only gradually at lower rates. The low complexity of this coding system shows its potential for interactive applications with levels of quality from good to perceptually transparent.

Citations