An adaptive wavelet-based approach for perceptual low bit rate audio coding attending to entropy-type criteria

This paper outlines an adaptive wavelet-based perceptual audio coding scheme attending to various entropy-type criteria. Its performance using some different wavelet families and various filter lengths and decomposition depths has also been investigated. An optimal choice of these parameters is accomplished in order to evaluate both quality and bit rate of compressed signals for four different entropy-type criteria and four representative samples of audio material. The proposed coding scheme performs a periodized wavelet packet transform for each audio frame leading to a decomposition tree which is adapted to the characteristics of the audio frame attending to some entropy criterion. After time-frequency mapping, a thresholding to zero step is carried out to take advantage of entropy coding methods. Next, an uniform quantifier controlled by a psychoacoustic model taking advantage of the masking effect in human hearing is used. Finally, statistical redundancies of audio signals are reduced by using Huffman and run length coding. Experimental results indicate that the proposed approach can achieve almost transparent coding of monophonic CD quality audio signals at bit rates of approximately 64 kb/s (1.45 bit/sample). In addition, the use of the periodized wavelet transform leads to lower coding delay than other similar methods in the literature. The performance of our method is compared to some non-adaptive wavelet-based methods and to MPEG standard in terms of compression versus quality performance. IMACS/IEEE CSCC'99 Proceedings, Pages:3441-3445 Key-Words: wavelet-based audio coding, psychoacoustic model, entropy-type criteria, MPEG