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

Adaptive Variable Degree-k Zero-Trees for Re-Encoding of Perceptually Quantized Wavelet-Packet Transformed Audio and High Quality Speech