An enhanced psychoacoustic model based on the discrete wavelet packet transform

The perception of acoustic information by humans is based on the detailed temporal and spectral analysis provided by the auditory processing of the received signal. The incorporation of this process in psychoacoustical computational models has contributed significantly both in the development of highly efficient audio compression schemes as well as in effective audio watermarking methods. In this paper, we present an approach based on the discrete wavelet packet transform, which closely mimics the multi-resolution properties of the human ear and also includes simultaneous and temporal auditory masking. Experimental results show that the proposed technique offers better masking capabilities and it reduces the signal-to-masking ratio when compared to related approaches, without introducing audible distortion. Those results have implications that are important both for audio compression by permitting further bit rate reduction, and for watermarking by providing greater signal space for information hiding.