Audio coding with a dynamic wavelet packet decomposition based on frequency-varying modulated lapped transforms

Optimum time-frequency decompositions are very useful in audio coding applications, because the signal energy can be maximally concentrated even for the wide variety of audio signal characteristics. Moreover, this signal representation is particularly well suited for a perceptual weighting of the quantization noise. The well known tree structure of cascaded 2-channel filterbanks allows a very flexible optimization, leading to a signal adaptive, dynamic wavelet packet decomposition. A major drawback of this technique are strong spectral side lobes which produce clearly audible aliasing in perceptual coders. We present a new dynamic wavelet packet decomposition, based on modulated lapped transforms, which allows the same flexibility while avoiding the disadvantage mentioned above. We propose a scheme for low bit rate audio coding that efficiently exploits the high energy concentration. This new codec yields excellent audio quality at about 55 kb/s for monophonic signals.

[1]  P. Noll,et al.  A new orthonormal wavelet packet decomposition for audio coding using frequency-varying modulated lapped transforms , 1995, Proceedings of 1995 Workshop on Applications of Signal Processing to Audio and Accoustics.

[2]  P. Noll,et al.  Digital audio coding for visual communications , 1995, Proc. IEEE.

[3]  S. Geneva,et al.  Sound Quality Assessment Material: Recordings for Subjective Tests , 1988 .

[4]  Deepen Sinha,et al.  Low bit rate transparent audio compression using adapted wavelets , 1993, IEEE Trans. Signal Process..

[5]  Ricardo L. de Queiroz,et al.  Time-varying lapped transforms and wavelet packets , 1993, IEEE Trans. Signal Process..

[6]  Robert J. Safranek,et al.  Signal compression based on models of human perception , 1993, Proc. IEEE.

[7]  Ronald R. Coifman,et al.  Entropy-based algorithms for best basis selection , 1992, IEEE Trans. Inf. Theory.

[8]  John Princen,et al.  Audio coding with signal adaptive filterbanks , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[9]  I. Daubechies Orthonormal bases of compactly supported wavelets , 1988 .