2. Digital Image Processing 3rd Edition
Rafael C.Gonzalez, Richard E.Woods
Prentice Hall, 2008

3. Table of Content Chapter 1 1.1 Introduction
1.2 The Origins of Digital Image processing
1.2 Examples of fields that use Digital Image Processing:
- Gamma ray Imaging
- Imaging in Ultra Violet Band
- Imaging in Visible and Infrared bands
- Imaging in Microwave Band
- Imaging in radio Band
- Some other examples

4. Table of Content Chapter 1
1.4 Fundamental Steps in Digital Image Processing
1.5 Components of an Image Processing System

5. Table of Content Chapter 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 relationship between Pixels
2.6 An introduction to mathematical tools used
in digital image processing

6. Table of Content Chapter 2 Digital Image Fundamentals
2.6 An introduction to mathematical tools used
in digital image processing
Array verses matrix operations
Linear verses nonlinear operations
Arithmetic operations
Set and Logical operation
Vectors and matrix operations
Image transforms
Probabilistic methods

7. Table of Content Chapter 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 Spatial Filters
3.6 Sharpening Spatial Filters
3.7 Combining Spatial Enhancement Methods
3.8 Using Fuzzy Techniques for Intensity Transformations
and Spatial Filtering

8. Table of Content Chapter 4 Filtering in Frequency Domain
4.1 Background
4.2 Preliminary Concepts (Introduction to Fourier Transform and
Frequency Domain)
4.3 Sampling and Fourier transform of Sampled Functions
4.4 Discrete Fourier Transform (DFT) of one Variable
4.5 Extension of functions of Two Variables
4.6 Some Properties of 2-D Discrete Fourier Transform
4.7 Basic of Filtering in Frequency Domain

9. Table of Content Chapter 4 Filtering in Frequency Domain
4.8 Image Smoothing using Frequency Domain Filters
4.9 Image Sharpening using Frequency Domain Filters
4.10 Selective Filtering
- Bandreject and Bandpass filters
- Notch Filtering
4.11 Implementation

10. Table of Content Chapter 4 Some other useful transforms
Walsh Transform
Hadamard Transform
Discrete Cosine Transform (DCT)
Principal Component Analysis (PCA)
Karhunen Loeve Transform (KLT)
Hotling Transform

11. Table of Content Chapter 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 by Frequency Domain Filtering
5.5 Linear, Position-Invariant Degradations
5.6 Estimating the Degradation Function

12. Table of Content Chapter 5 Image Restoration 5.7 Inverse Filtering
Minimum Mean Square (Winner) Filtering
Constrained Least Squares Filtering
5.10 Geometric Mean Filter
5.11 Image Reconstruction from Projections

13. Table of Content Chapter 5 Image Restoration
How to find linear motion blur and out of focus blur
parameters and then restore such
degraded images

14. Table of Content Chapter 6 Color Image processing
6.1 Color Fundamentals
6.2 Color Models
6.3 Pseudo-color Image processing
6.4 Basics of Full-Color Image Processing
6.5 Color Transformation

15. Table of Content Chapter 6 Color Image processing
6.6 Smoothing and Sharpening
6.7 Image Segmentation based on Color
6.8 Noise in Color Images
6.9 Color Image Compression

16. Table of Content
Chapter 7 Waelets and Multiresolution Processing

17. Chapter 8 Image Compression
- Fundamentals
- Coding redundancy
- Spatial and temporal redundancy
- Irrelevant information
- Measuring image information
- Fidelity criteria
- Image compression methods
- Image formats, Containers and compression standards

18. Chapter 8 Image Compression
- Some basic Compression methods
- Huffman coding
- Arithmetic Coding
- LZW coding
- Run length coding
- Symbol-based coding
- Bit-plane coding
- Block transform coding
- Predictive coding
- Wavelet coding
- Digital Image watermarking

19. Chapter 8 Image Compression
- Digital Image watermarking

20. Chapter-9 Binary Image Analysis
Binary Image Morphology
Structuring element
Basic morphological operations
Dilation and Erosion
Opening and Closing
The Hit-or-Miss transformation

21. Chapter-9 Binary Image Analysis
Some basic morphological algorithms
Boundary extraction
Hole filling
Extraction of connected components
Convex Hull
Thinning
Thickening
Skeleton
Pruning

22. Table of Content Chapter 10 Image Segmentation
Chapter 11 Representation and Description
Chapter 12 Object Recognition

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