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This book concerns modern methods in scientific computing and linear algebra, relevant to image and signal processing. For these applications, it is important to consider ingredients such as: (1) sophisticated mathematical models of the problems, including a priori knowledge, (2) rigorous mathematical theories to understand the difficulties of solving problems which are ill-posed, and (3) fast algorithms for either real-time or data-massive computations. Such are the topics brought into focus by these proceedings of the Workshop on Scientific Computing (held in Hong Kong on March 10-12, 1997, the sixth in such series of Workshops held in Hong Kong since 1990), where the major themes were on numerical linear algebra, signal processing, and image processing. Readers will benefit from the lectures presented on the recent advances, trends and future directions for research in fast algorithms in scientific computing, written by leading experts in the field from around the world.
Sommario
Invited Papers: Tikhonov regularization for large scale problems (GH Golub & U von Matt); Numerical stability of some fast algorithms for structured matrices (RP Brent); The role of coordinates in accurate computation of discontinuous flow (WH Hui); Regularized blind deconvolution using recursive inverse filtering (MK Ng et al); Solution of linear systems arising in nonlinear image deblurring (CR Vogel); and other papers. Contributed Papers: 3-D Jacobi rotation method for eigenvalue problems of matrices (DY Cai & WM Xue); Wavelets, signal processing and textile surfaces (H Kraus); Efficient image compression scheme using tree structure wavelet transforms (JM Li & JS Jin); A note on adaptive restarting procedure for pseudo residual algorithms (T Nodera & T Inadu); Adaptive mthods for singular pertubation problems (T Tang & DM Sloan); Image recontruction from projections based on wavelet decomposition (JH Yin); and other papers.
