Wavelet-based approach for transient modeling with application to parametric audio coding

In this paper we intend to optimize a wavelet-based dictionary for transient modeling with application to parametric audio coding. Transient modeling is performed by matching pursuit with an overcomplete dictionary composed of orthonormal wavelet functions that implement a wavelet-packet filter bank. We try to find the prototype filter length, the decomposition depth and the orthogonal wavelet family that lead to the best balance between mean squared error and computational cost. We are also interested in the structure of the wavelet decomposition tree. In such sense, comparison between the wavelet transform and the full wavelet-packet transform is performed. Finally, comparative analysis between wavelets and exponentially damped sinusoids is shown in experimental results. The proposed transient modeling method is suitable to be integrated into a parametric audio coder based on the three-part model of sines, transients and noise (STN model).