Charles Chui is a Curators' Professor in the Department of Mathematics and Computer Science at the University of Missouri in St. Louis, and a consulting professor of statistics at Stanford University in California. Dr. Chui's research interests encompass applied and computational mathematics, with an emphasis on splines, wavelets, mathematics of imaging, and fast algorithms. Johan de Villiers is a professor in the Department of Mathematical Sciences, Mathematics Division at Stellenbosch University in South Africa. Dr. de Villiers's research interests include computational mathematics, with an emphasis on wavelet and subdivision analysis.
The monograph contains many examples, figures, and more than 300 exercises. It is friendly written for a broad readership and very convenient for students and researchers in applied mathematics and computer science. Doubtless, this nice book will stimulate further research in modeling of curves and surfaces with wavelet subdivision methods. --Manfred Tasche, Zentralblatt MATH 1202 All topics are treated with great care, and a lot of effort is put into stating results and proofs with a very high precision and accuracy. This makes the book so self-contained that its list of references consists of only 24 items. This is exceptional for a monograph of 450 pages and quite clearly shows the intention of the authors and the approach they have taken for their book. ! the book provides everything that is useful, for example, for classroom use: examples, exercises (even with marked difficulty levels), a carefully compiled index and even a very impressive reading guide. ! Its extraordinary attention to detail makes it useful to undergraduate students or researchers who want to get familiar with the fundamental techniques of stationary subdivision, who want to see how the machine works inside . --Tomas Sauer, Mathematical Reviews, Issue 2011k This book is the first writing that introduces and incorporates the wavelet component of the bottom-up subdivision scheme. A complete constructive theory, together with effective algorithms, is developed to derive such synthesis wavelets and analysis wavelet filters. The book contains a large collection of carefully prepared exercises and can be used both for classroom teaching and for self study. The authors have been in the forefront for advances in wavelets and wavelet subdivision methods and I congratulate them for writing such a comprehensive text. --From the Foreword by Tom Lyche, University of Oslo, Norway