Mathematics of digital images : creation, compression, restoration, recognition S.G. Hoggar.

Compression, restoration and recognition are three of the key components of digital imaging. The mathematics needed to understand and carry out all these components are explained here in a textbook that is both rigorous and practical, with many worked examples, exercises with solutions, pseudocode and sample calculations on images. The introduction gives fast tracks to special topics such as principal component analysis, and points the reader through the book, which abounds with illustrations. The first part of the volume describes plane geometry and pattern-generating symmetries, along with some text on 3-D rotation and reflection matrices. Subsequent chapters cover vectors, matrices and probability, which are then applied to simulation, Bayesian methods, Shannon's information theory, compression, filtering and tomography. The book is suitable for course use or for self-study and will appeal to all those working in biomedical imaging and diagnosis, computer graphics, machine vision, remote sensing, image processing and information theory and its applications.