Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods is the industry’s most prized foundational text, celebrating 40 years as the definitive guide to the study of digital image processing. This 4th Edition is specifically designed for college seniors and first-year graduate students with a background in mathematical analysis, vectors, matrices, probability, statistics, linear systems, and computer programming. Maintaining its core focus on fundamentals, this edition has been extensively updated based on global feedback from faculty and students in over 150 institutions.
This edition introduces significant new coverage of cutting-edge topics, including deep learning and deep neural networks with a focus on convolutional neural nets. It also explores advanced concepts such as the scale-invariant feature transform (SIFT), maximally-stable extremal regions (MSERs), graph cuts, k-means clustering, superpixels, and active contours (snakes and level sets). Major enhancements have been made to the organization of image transforms, spatial kernels, and spatial filtering, ensuring a more cohesive and comprehensive learning experience.
To support practical application, the text features revised examples and homework exercises, along with the addition of MATLAB projects at the end of every chapter. These resources provide a robust framework for mastering both the theoretical and practical aspects of the field, making it an essential resource for anyone serious about the study of image processing.
Book Details:
- Author: Rafael C. Gonzalez, Richard E. Woods
- Edition: 4th Edition
- Publisher: Pearson
- Publication Date: March 20, 2017
- ISBN-10: 9780133356724
- ISBN-13: 978-0-133356724