A general biorthogonal wavelet based on Karhunen–Loéve transform approximation. Issue 4 (April 2016) - Kale, Mehmet
Abstract The lifting style biorthogonal wavelet implementation has a nice property of enabling flexible design; it is immediately reversible and has a simple relation to subband filters. In this work, we present a general wavelet prediction (P ) and update (U ) filters of two-channel lifting structures. A previous research of the author introduced signal-specific wavelets, which minimizes the difference between block wavelet transform matrix of the wavelet and the Karhunen–Loéve transform of a stochastic process with certain autocorrelation sequence. This research introduces a general wavelet, which can work on any stochastic process. Numerical results are provided in terms of the filter coefficients and experimental performances on 16 test images.