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Digital Image Processing, 4th edition



About the Book

Basic Information

  • ISBN number 9780133356724.

  • Publisher: Pearson

  • 13 chapters.

  • 1168 pages.

  • 2018.

DIGITAL IMAGE 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 MATLAB 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 institutions 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 detection.

  • A discussion of clustering, superpixels, graph cuts, and their use in region segmentation.

  • New material on active contours that includes snakes and level sets, and their
    use in image segmentation.

  • Coverage of maximally stable extremal regions.

  • Expanded coverage of feature extraction to include the Scale Invariant Feature
    Transform (SIFT).

  • Expanded coverage of neural networks to include deep neural networks, backpropagation,
    deep learning, and, especially, deep convolutional neural networks.

  • More homework problems at the end of the chapters.

  • MATLAB computer projects.

Please click here for more details.