Description

Book Synopsis


Table of Contents
  • 1 Introduction
  • 1.1 What is Digital Image Processing?
  • 1.2 The Origins of Digital Image Processing
  • 1.3 Examples of Fields that Use Digital Image Processing
  • 1.4 Fundamental Steps in Digital Image Processing
  • 1.5 Components of an Image Processing System
  • 2 Digital Image Fundamentals
  • 2.1 Elements of Visual Perception
  • 2.2 Light and the Electromagnetic Spectrum
  • 2.3 Image Sensing and Acquisition
  • 2.4 Image Sampling and Quantization
  • 2.5 Some Basic Relationships Between Pixels
  • 2.6 Introduction to the Basic Mathematical Tools Used in Digital Image Processing
  • 3 Intensity Transformations and Spatial Filtering
  • 3.1 Background
  • 3.2 Some Basic Intensity Transformation Functions
  • 3.3 Histogram Processing
  • 3.4 Fundamentals of Spatial Filtering
  • 3.5 Smoothing (Lowpass) Spatial Filters
  • 3.6 Sharpening (Highpass) Spatial Filters
  • 3.7 Highpass, Bandreject, and Bandpass Filters from Lowpass Filters
  • 3.8 Combining Spatial Enhancement Methods
  • 3.9 Using Fuzzy Techniques for Intensity Transformations and Spatial Filtering
  • 4 Filtering in the Frequency Domain
  • 4.1 Background
  • 4.2 Preliminary Concepts
  • 4.3 Sampling and the Fourier Transform of Sampled Functions
  • 4.4 The Discrete Fourier Transform of One Variable
  • 4.5 Extensions to Functions of Two Variables
  • 4.6 Some Properties of the 2-D DFT and IDFT
  • 4.7 The Basics of Filtering in the Frequency Domain
  • 4.8 Image Smoothing Using Lowpass Frequency Domain Filters
  • 4.9 Image Sharpening Using Highpass Filters
  • 4.10 Selective Filtering
  • 4.11 The Fast Fourier Transform
  • 5 Image Restoration and Reconstruction
  • 5.1 A Model of the Image Degradation/Restoration Process
  • 5.2 Noise Models
  • 5.3 Restoration in the Presence of Noise Only—Spatial Filtering
  • 5.4 Periodic Noise Reduction Using Frequency Domain Filtering
  • 5.5 Linear, Position-Invariant Degradations
  • 5.6 Estimating the Degradation Function
  • 5.7 Inverse Filtering
  • 5.8 Minimum Mean Square Error (Wiener) Filtering
  • 5.9 Constrained Least Squares Filtering
  • 5.10 Geometric Mean Filter
  • 5.11 Image Reconstruction from Projections
  • 6 Wavelet and Other Image Transforms
  • 6.1 Preliminaries
  • 6.2 Matrix-based Transforms
  • 6.3 Correlation
  • 6.4 Basis Functions in the Time-Frequency Plane
  • 6.5 Basis Images
  • 6.6 Fourier-Related Transforms
  • 6.7 Walsh-Hadamard Transforms
  • 6.8 Slant Transform
  • 6.9 Haar Transform
  • 6.10 Wavelet Transforms
  • 7 Color Image Processing
  • 7.1 Color Fundamentals
  • 7.2 Color Models
  • 7.3 Pseudocolor Image Processing
  • 7.4 Basics of Full-Color Image Processing
  • 7.5 Color Transformations
  • 7.6 Color Image Smoothing and Sharpening
  • 7.7 Using Color in Image Segmentation
  • 7.8 Noise in Color Images
  • 7.9 Color Image Compression
  • 8 Image Compression and Watermarking
  • 8.1 Fundamentals
  • 8.2 Huffman Coding
  • 8.3 Golomb Coding
  • 8.4 Arithmetic Coding
  • 8.5 LZW Coding
  • 8.6 Run-length Coding

Digital Image Processing Global Edition

Product form

£74.09

Includes FREE delivery

RRP £77.99 – you save £3.90 (5%)

Order before 4pm today for delivery by Sat 20 Dec 2025.

A Paperback / softback by Rafael Gonzalez, Richard Woods

7 in stock


    View other formats and editions of Digital Image Processing Global Edition by Rafael Gonzalez

    Publisher: Pearson Education Limited
    Publication Date: 26/10/2017
    ISBN13: 9781292223049, 978-1292223049
    ISBN10: 1292223049
    Also in:
    Computing Image processing Technology, Engineering & Agriculture Electrical engineering

    Description

    Book Synopsis


    Table of Contents
    • 1 Introduction
    • 1.1 What is Digital Image Processing?
    • 1.2 The Origins of Digital Image Processing
    • 1.3 Examples of Fields that Use Digital Image Processing
    • 1.4 Fundamental Steps in Digital Image Processing
    • 1.5 Components of an Image Processing System
    • 2 Digital Image Fundamentals
    • 2.1 Elements of Visual Perception
    • 2.2 Light and the Electromagnetic Spectrum
    • 2.3 Image Sensing and Acquisition
    • 2.4 Image Sampling and Quantization
    • 2.5 Some Basic Relationships Between Pixels
    • 2.6 Introduction to the Basic Mathematical Tools Used in Digital Image Processing
    • 3 Intensity Transformations and Spatial Filtering
    • 3.1 Background
    • 3.2 Some Basic Intensity Transformation Functions
    • 3.3 Histogram Processing
    • 3.4 Fundamentals of Spatial Filtering
    • 3.5 Smoothing (Lowpass) Spatial Filters
    • 3.6 Sharpening (Highpass) Spatial Filters
    • 3.7 Highpass, Bandreject, and Bandpass Filters from Lowpass Filters
    • 3.8 Combining Spatial Enhancement Methods
    • 3.9 Using Fuzzy Techniques for Intensity Transformations and Spatial Filtering
    • 4 Filtering in the Frequency Domain
    • 4.1 Background
    • 4.2 Preliminary Concepts
    • 4.3 Sampling and the Fourier Transform of Sampled Functions
    • 4.4 The Discrete Fourier Transform of One Variable
    • 4.5 Extensions to Functions of Two Variables
    • 4.6 Some Properties of the 2-D DFT and IDFT
    • 4.7 The Basics of Filtering in the Frequency Domain
    • 4.8 Image Smoothing Using Lowpass Frequency Domain Filters
    • 4.9 Image Sharpening Using Highpass Filters
    • 4.10 Selective Filtering
    • 4.11 The Fast Fourier Transform
    • 5 Image Restoration and Reconstruction
    • 5.1 A Model of the Image Degradation/Restoration Process
    • 5.2 Noise Models
    • 5.3 Restoration in the Presence of Noise Only—Spatial Filtering
    • 5.4 Periodic Noise Reduction Using Frequency Domain Filtering
    • 5.5 Linear, Position-Invariant Degradations
    • 5.6 Estimating the Degradation Function
    • 5.7 Inverse Filtering
    • 5.8 Minimum Mean Square Error (Wiener) Filtering
    • 5.9 Constrained Least Squares Filtering
    • 5.10 Geometric Mean Filter
    • 5.11 Image Reconstruction from Projections
    • 6 Wavelet and Other Image Transforms
    • 6.1 Preliminaries
    • 6.2 Matrix-based Transforms
    • 6.3 Correlation
    • 6.4 Basis Functions in the Time-Frequency Plane
    • 6.5 Basis Images
    • 6.6 Fourier-Related Transforms
    • 6.7 Walsh-Hadamard Transforms
    • 6.8 Slant Transform
    • 6.9 Haar Transform
    • 6.10 Wavelet Transforms
    • 7 Color Image Processing
    • 7.1 Color Fundamentals
    • 7.2 Color Models
    • 7.3 Pseudocolor Image Processing
    • 7.4 Basics of Full-Color Image Processing
    • 7.5 Color Transformations
    • 7.6 Color Image Smoothing and Sharpening
    • 7.7 Using Color in Image Segmentation
    • 7.8 Noise in Color Images
    • 7.9 Color Image Compression
    • 8 Image Compression and Watermarking
    • 8.1 Fundamentals
    • 8.2 Huffman Coding
    • 8.3 Golomb Coding
    • 8.4 Arithmetic Coding
    • 8.5 LZW Coding
    • 8.6 Run-length Coding

    Recently viewed products

    © 2025 Book Curl

      • American Express
      • Apple Pay
      • Diners Club
      • Discover
      • Google Pay
      • Maestro
      • Mastercard
      • PayPal
      • Shop Pay
      • Union Pay
      • Visa

      Login

      Forgot your password?

      Don't have an account yet?
      Create account