Proposal of an adaptive analysis/synthesis scheme in the time-frequency plane based on entropy criteria: application to transform-based audio coding.

Summary The adapted representations contribute to the study and processing of the information carried by the signals by allowing a different relevant analysis for each signal. This thesis work deals with the development of a representation using successively temporal and frequency segmentations adapted to the signal, which is more flexible than existing solutions. This scheme is applied in a perceptual encoder by high fidelity transform. The signal is first temporally segmented. The criterion used is based on a local entropy estimator, which provides an index of variations, conducive to an automatic segmentation separating transient and stationary areas. The temporal slices thus delimited are then decomposed into wavelet packets and a search for the best basis allows the frequency adaptation of the representation. An extension of the best basis search is proposed to increase the dictionary of available bases compared to the dyadic case. At the end of this analysis the signal is localized in atoms of the time-frequency plane. An original architecture coder including our representation is then presented, as well as the details of its implementation. This encoder is evaluated by subjective tests comparing the compressed sounds to the originals and to the MPEG1-III standard for a bit rate of 96 kbit/s. The results show that the use of the adapted representation scheme in an encoder is competitive with standard encoder solutions while many improvements are possible.