New methods for lossy image compression based on generalized wavelet decompositions have been introduced recently. Unlike in the classical wavelet decomposition scheme, it is possible to use different scaling and wavelet functions at every scale by using nonstationary multiresolution analyses. This freedom in using different functions can be exploited for adaptive compression techniques. We extend this approach to arbitrary subbands (e.g., in a wavelet packet scheme), combine it with the best basis algorithm, and introduce efficient techniques for using these algorithms on parallel computers.
Andreas Uhl, Andreas Uhl,
"Generalized wavelet decompositions in image compression: arbitrary subbands and parallel algorithms," Optical Engineering 36(5), (1 May 1997). https://doi.org/10.1117/1.601338