This book is concerned with linear and nonlinear transformations of digitized images and patterns. Transformation models include linear, quadratic, cubic, bilinear, biquadratic, bicubic, Coons model and other nonlinear forms such as harmonic, projective, and perspective transformations. Discrete techniques have been developed to realize both forward and inverse transformations. The latter can be applied to normalize distorted images and to enhance the pattern recognition process. Efficient algorithms such as the splitting-shooting methods and splitting-integrating methods have been developed and analysed in this book for the first time. Graphical examples are given and compared with existing algorithms. This book is of interest to researchers in the areas of pattern recognition, character recognition, image processing, computer vision, computer graphics and other related fields.