Signal-matched wavelet design via lifting using optimization techniques

This paper proposes design of signal-matched wavelets via lifting. The design is modular owing to lifting framework wherein both predict and update stage polynomials are obtained from the given signal. Successive predict stages are designed using the least squares criterion, while the update stages are designed with total variation minimization on the wavelet approximation coefficients. Different design strategies for compression and denoising are presented. The efficacy of matched-wavelets is illustrated on transform coding gain and signal denoising.