Marking a distinct departure from the perspectives of frame theory and discrete transforms, this book provides a comprehensive mathematical and algorithmic introduction to wavelet theory. As such, it can be used as either a textbook or reference guide.
As a textbook for graduate mathematics students and beginning researchers, it offers detailed information on the basic theory of framelets and wavelets, complemented by self-contained elementary proofs, illustrative examples/figures, and supplementary exercises.
Lastly, the book can also be used to teach on or study selected special topics in approximation theory, Fourier analysis, applied harmonic analysis, functional analysis, and wavelet-based signal/image processing.
Algorithmic approach to framelets and wavelets with self-contained proofs and illustrative examples
Comprehensive treatments on refinable vector functions and theory of multiframelets/multiwavelets
Recent advances on wavelet-based applications such as directional framelets for image processing
Bin Han
framelets and wavelets discrete framalet/wavelet transform orthogonal and biorthogonal wavelets tight and dual framelets wavelet and framelet filter banks nonhomogeneous and homogeneous affine systems refinable structure refinable vector functions mulitframelets and multiwavelets refinable splines linear independence and stability cascade algorithms and subdivision schemes sum rules vanishing moments linear-phase moments