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

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    A Paperback / softback by Rafael Gonzalez, Richard Woods

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      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

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