Digital Image Processing, 4th edition

  • Rafael C. Gonzalez, 
  • Richard E. Woods

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Digital Imaging Processing provides a clear, definitive overview of the subject, focusing on fundamental skills and concepts. For the 4th Edition, authors Rafael Gonzalez and Richard Woods revised their text based on an extensive survey of faculty, students and independent readers in 150 institutions from 30 countries.

The 4th Edition offers expanded or new coverage of deep learning, the scale-invariant feature transform (SIFT), graph cuts, active contours, exact histogram matching and many other topics. More cohesive presentations on image transforms, spatial kernels and spatial filtering illuminate these key topics. In addition, this edition features MATLAB projects at the end of every chapter.

Published by Pearson (January 1st 2022) - Copyright © 2016

ISBN-13: 9780137848560

Subject: Electrical Engineering

Category: Image Processing

Table of contents

1. Introduction

What Is Digital Image Processing?

The Origins of Digital Image Processing

Examples of Fields that Use Digital Image Processing

Fundamental Steps in Digital Image Processing

Components of an Image Processing System

2. Digital Image Fundamentals

Elements of Visual Perception

Light and the Electromagnetic Spectrum. Image Sensing and Acquisition

Image Sampling and Quantization

Some Basic Relationships Between Pixels

An Introduction to the Mathematical Tools Used in Digital Image Processing

3. Intensity Transformations and Spatial Filtering


Some Basic Intensity Transformation Functions

Histogram Processing. Fundamentals of Spatial Filtering

Smoothing Spatial Filters

Sharpening Spatial Filters

Combining Spatial Enhancement Methods

Using Fuzzy Techniques for Intensity Transformations and Spatial Filtering

4. Filtering in the Frequency Domain


Preliminary Concepts

Sampling and the Fourier Transform of Sampled Functions

The Discrete Fourier Transform (DFT) of One Variable

Extension to Functions of Two Variables

Some Properties of the 2-D Discrete Fourier Transform

The Basics of Filtering in the Frequency Domain

Image Smoothing Using Frequency Domain Filters

Image Sharpening Using Frequency Domain Filters

Selective Filtering


5. Image Restoration and Reconstruction

A Model of the Image Degradation/Restoration Process

Noise Models

Restoration in the Presence of Noise Only–Spatial Filtering

Periodic Noise Reduction by Frequency Domain Filtering

Linear, Position-Invariant Degradations. Estimating the Degradation Function

Inverse Filtering

Minimum Mean Square Error (Wiener) Filtering

Constrained Least Squares Filtering. Geometric Mean Filter

Image Reconstruction from Projections.

6. Color Image Processing

Color Fundamentals

Color Models

Pseudocolor Image Processing

Basics of Full-Color Image Processing

Color Transformations. Smoothing and Sharpening

Image Segmentation Based on Color

Noise in Color Images

Color Image Compression

7. Wavelets and Multiresolution Processing


Multiresolution Expansions

Wavelet Transforms in One Dimension

The Fast Wavelet Transform

Wavelet Transforms in Two

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