Digital Image Processing, 4th edition
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Overview
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
Background
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
Background
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
Implementation
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
Background
Multiresolution Expansions
Wavelet Transforms in One Dimension
The Fast Wavelet Transform
Wavelet Transforms in Two
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