In its original form, the wavelet transform is a linear tool. However, it has been increasingly recognized that nonlinear extensions are possible. A major impulse to the development of nonlinear wavelet transforms has been given by the introduction of the lifting scheme by Sweldens. The aim of this report, which is a sequel to a previous report devoted exclusively to the pyramid transform, is to present an axiomatic framework encompassing most existing linear and nonlinear wavelet decompositions. Furthermore, it introduces some, thus far unknown, wavelets based on mathematical morphology, such as the morphological Haar wavelet, both in one and two dimensions. A general and flexible approach for the construction of nonlinear (morphological) wavelets is provided by the lifting scheme. This paper discusses one example in considerable detail, the max-lifting scheme, which has the intriguing property that it preserves local maxima in a signal over a range of scales, depending on how local or global these maxima are.
Additional Metadata
Keywords Multiresolution signal processing and analysis, Morphological Haar wavelet, Median operator, Max-lifting, Mathematical morphology, Lifting scheme, Coupled and uncoupled wavelet decompositions, Biorthogonal linear wavelets, Analysis and synthesis operators
Publisher CWI
Series CWI. Probability, Networks and Algorithms [PNA]
Citation
Heijmans, H.J.A.M, & Goutsias, J. (1999). Multiresolution signal decomposition schemes. Part 2: Morphological wavelets. CWI. Probability, Networks and Algorithms [PNA]. CWI.