We investigate central issues such as invertibility, stability, synchronization, and frequency characteristics for nonlinear wavelet transforms built using the lifting framework. The nonlinearity comes from adaptively choosing between a class of linear predictors within the lifting framework. We also describe how earlier families of nonlinear filter banks can be extended through the use of prediction functions operating on a causal neighborhood of pixels. Preliminary compression results for model and real-world images demonstrate the promise of our techniques.
['Roger L. Claypoole', 'Geoffrey Davis', 'Wim Sweldens', 'Richard G. Baraniuk']
Nonlinear wavelet transforms for image coding via lifting