Perfect reconstructional multidimensional filter banks with time-varying basis functions

Many multidimensional signals of interest are nonstationary and thus have statistical characteristics that change temporally and/or spatially. It is reasonable to expect that time-varying transforms can better model M-D signals than time-invariant ones. We discuss time-varying multidimensional filter banks with adaptive filter coefficients. The focus is on the design of exact reconstructing multidimensional adaptive filter banks. We extend our 1-D time-varying filter bank design method to multiple dimensions to consider the design of perfect reconstructing time-varying nonseparable filter banks. The resulting design method is simple, elegant and extremely powerful