PROCESSING has been the world's leading textbook in its
field for more than 40 years. As in the 1977 and 1987 editions by Gonzalez
and Wintz, and the 1992, 2002, and 2008 editions by Gonzalez and Woods, this
sixth-generation edition was prepared with students and instructors in mind.
The principal objectives of the book continue to be to provide an
introduction to basic concepts and methodologies applicable to digital image
processing, and to develop a foundation that can be used as the basis for
further study and research in this field. The
material is timely, highly readable, and illustrated with numerous examples
of practical significance. All mainstream areas of image processing are
covered, including image fundamentals; image filtering and enhancement in the spatial and
frequency domains; image restoration and reconstruction; color image processing; wavelets
and other image transforms; image
compression and watermarking; morphology; segmentation using "classical"
methods; segmentation using graph cuts, superpixels, snakes, and level sets; image
feature extraction, including the scale-invariant image transform (SIFT);
and image pattern classification, including fully-connected and
convolutional neural networks, and deep learning.
Although the book is completely self-contained, this companion web site
provides additional support in the form of review material, answers to
selected problems, laboratory project suggestions, and a score of other
features. For the first time we have added
projects at the end of every chapter, and have organized
all support materials in the form of
DIP4E Support Packages
for students and faculty.
See also a partial list of
that use the book.
One of the principal reasons this book has been the world leader in its
field for more than 40 years is the level of attention we pay to the
changing educational needs of our readers. The present edition is based on
an extensive survey involving
faculty, students, and independent readers of the book in 150 institutions
from 30 countries. Many of the following new features are based on the
results of that survey.
New material related to histogram matching.
Expanded coverage of the fundamentals of spatial filtering.
A more comprehensive and cohesive coverage of image transforms.
A more complete presentation of finite differences, with a focus on edge
A discussion of clustering, superpixels, graph cuts, and their use in
New material on active contours that includes snakes and level sets, and
use in image segmentation.
Coverage of maximally stable extremal regions.
Expanded coverage of feature extraction to include the Scale Invariant
Expanded coverage of neural networks to include deep neural networks,
deep learning, and, especially, deep convolutional neural networks.
More homework problems at the end of the chapters.
MATLAB computer projects.
here for more