  The constant center frequency to bandwidth ratio (Q-factor) of wavelet
transforms provides a very natural representation for audio data. However,
invertible wavelet transforms have either required non-uniform decimation --
leading to irregular data structures that are cumbersome to work with -- or
require excessively high oversampling with unacceptable computational overhead.
Here, we present a novel decimation strategy for wavelet transforms that leads
to stable representations with oversampling rates close to one and uniform
decimation. Specifically, we show that finite implementations of the resulting
representation are energy-preserving in the sense of frame theory. The obtained
wavelet coefficients can be stored in a timefrequency matrix with a natural
interpretation of columns as time frames and rows as frequency channels. This
matrix structure immediately grants access to a large number of algorithms that
are successfully used in time-frequency audio processing, but could not
previously be used jointly with wavelet transforms. We demonstrate the
application of our method in processing based on nonnegative matrix
factorization, in onset detection, and in phaseless reconstruction.
