Signal-based design of wavelet filters

We address optimization and adaptation issues in designing the best wavelet filters for the representation or the compression of a given signal. A signal-based optimization technique is proposed and the application of this technique using different optimization criteria, corresponding to energy compaction, is considered. When applying this strategy to textures, for region-based image compression, we show that significant gain in a rate-distortion sense is achievable: up to 1.2 dB improvement is to be expected when compared to usual efficient filters (optimal in coding gain for AR(1) models). The choice of the optimization criterion is discussed for optimal performances in the rate-distortion sense.