As befits a modern introduction to this topic, a good balance is struck between discussing the underlying mathematics and the main topics of signal processing, data discretization, the theory of color and different color systems, operations in images, dithering and half-toning, warping and morphing, and image processing. Significantly expanded and revised, this easy-to-follow text/reference reflects recent trends in science and technology that exploit image processing in computer graphics and vision applications. Stochastic image models and statistical methods for image processing are covered, as is probability theory for image processing, and a focus on applications in image analysis and computer vision.

Features:

. Includes 5 new chapters and major changes throughout

. Adopts a conceptual approach with emphasis on the mathematical concepts and their applications

.Introduces an abstraction paradigm that relates mathematical models with image processing techniques and implementation methods - used throughout to help understanding of the mathematical theory and its practical use

. Motivates through an elementary presentation, opting for an intuitive description where needed

. Contains adopted innovative formulations whenever necessary for clarity of exposition

. Provides numerous examples and illustrations, as an aid to understanding

. Focuses on the aspects of image processing that have importance in computer graphics and vision applications

. Offers a comprehensive introductory chapter for instructors

Thiscomprehensive text imparts a good conceptual understanding of the topic, as a basis for further study, and is suitable both as a textbook and a professional reference. The current extended edition is a must-have resource and guide for all studying or interested in this field.