  A fast, efficient and scalable algorithm is proposed, in this paper, for
re-encoding of perceptually quantized wavelet-packet transform (WPT)
coefficients of audio and high quality speech and is called "adaptive variable
degree-k zero-trees" (AVDZ). The quantization process is carried out by taking
into account some basic perceptual considerations, and achieves good subjective
quality with low complexity. The performance of the proposed AVDZ algorithm is
compared with two other zero-tree-based schemes comprising: 1- Embedded
Zero-tree Wavelet (EZW) and 2- The set partitioning in hierarchical trees
(SPIHT). Since EZW and SPIHT are designed for image compression, some
modifications are incorporated in these schemes for their better matching to
audio signals. It is shown that the proposed modifications can improve their
performance by about 15-25%. Furthermore, it is concluded that the proposed
AVDZ algorithm outperforms these modified versions in terms of both output
average bit-rates and computation times.
