Describes the principles and techniques of image processing using MATLAB. Every chapter is accompanied by a collection of exercises and programming assignments. The book is augmented with supplementary MATLAB codeand hints and solutions to problems are also provided.
Author(s): P. K. Thiruvikraman
Series: IOP Expanding Physics
Publisher: IOP Publishing
Year: 2020
Language: English
Pages: 300
City: Boca Raton
PRELIMS.pdf
Preface
Acknowledgments
Author biography
P K Thiruvikraman
CH001.pdf
Chapter 1 Introduction
1.1 The scope and importance of digital image processing
1.2 Images
1.3 Digital images
1.4 Processes involved in image processing and recognition
1.5 Applications of image processing
Exercises
CH002.pdf
Chapter 2 Image enhancement in the spatial domain
2.1 Enhancement of contrast
2.2 Gray level transformations
2.2.1 Thresholding
2.2.2 Power law, log, and exp transformations
2.2.3 Piecewise linear transformations
2.2.4 Gray level slicing
2.3 Bit plane slicing
2.4 Histogram processing
2.4.1 Histogram equalization
2.4.2 Histogram specification
2.5 Filtering in the spatial domain
2.5.1 Averaging
2.5.2 Median filter
2.6 Sharpening in the spatial domain
Exercises:
CH003.pdf
Chapter 3 Filtering in the Fourier domain
3.1 From the Fourier series to the Fourier transform
3.2 Meaning of the Fourier transform
3.3 The impulse function
3.4 Fourier transform of a train of impulses
3.5 The convolution theorem
3.6 The discrete Fourier transform (DFT)
3.7 Additional properties of the DFT
3.8 Filtering in the Fourier domain
3.9 Low-pass filters
3.10 Other low-pass filters
3.11 High-pass filters
3.12 The FFT
3.13 Comparison of the FFT with convolution
Exercises
CH004.pdf
Chapter 4 Image compression
4.1 Basics of image compression
4.2 Basics of coding theory
4.3 Uniquely decodable codes (UDCs), instantaneously decodable codes (IDCs), and all that
4.4 Kraft’s inequality
4.5 Efficiency of instantaneous codes
4.6 Information theory
4.7 Huffman coding: algorithm
4.8 Huffman coding: implementation
4.9 Nearly optimal codes
4.9.1 B code
4.9.2 Shift codes
4.9.3 Shannon–Elias–Fano coding
4.10 Reducing interpixel redundancy: run-length coding
4.10.1 Other methods for reducing interpixel redundancy
4.11 LZW coding
4.12 Arithmetic coding
4.13 Transform coding
Exercises
CH005.pdf
Chapter 5 Image analysis and object recognition
5.1 Image analysis
5.2 Detection of points and lines
5.3 The Hough transform
5.4 Segmentation: edge detection
5.4.1 The Marr–Hildreth edge detection algorithm
5.4.2 The Canny edge detector
5.5 Thresholding
5.6 A global view of image analysis and pattern recognition
5.7 Representation of objects
5.7.1 Chain codes
5.7.2 Signatures
5.7.3 Statistical moments
5.7.4 Regional descriptors
5.8 Texture
5.9 Skeletonization or medial axis transformation (MAT)
5.10 Principal component analysis (PCA)
5.10.1 PCA for color images
5.10.2 Image reconstruction from principal components
5.10.3 Application of PCA for optical character recognition (OCR)
5.11 Pattern recognition
CH006.pdf
Chapter 6 Image restoration
6.1 Analyzing motion blur
6.2 Inverse filtering
6.3 Noise
6.4 Removal of noise by morphological operations
6.4.1 Erosion
6.4.2 Dilation
6.4.3 Opening and closing
6.5 Alternative method for extracting and labeling connected components
6.6 Image reconstruction from projections
6.6.1 CT scan
6.6.2 The Radon transform
6.6.3 The Fourier slice theorem
Exercises
CH007.pdf
Chapter 7 Wavelets
7.1 Wavelets versus the Fourier transform
7.2 The Haar wavelet transform
7.3 An alternative view of wavelets
Exercises
CH008.pdf
Chapter 8 Color image processing
8.1 The RGB color model
8.2 The CMY and CMYK color models
8.3 The hue, saturation, and intensity (HSI) color model
Exercises
CH009.pdf
Chapter 9 Introduction to MATLAB®
9.1 Introduction
9.2 Help with MATLAB®
9.3 Variables
9.4 Mathematical operations
9.5 Loops and control statements
9.6 Built-in MATLAB® functions
9.7 Some more useful MATLAB® commands and programming practices
9.8 Functions
CH010.pdf
Chapter 10 The image processing toolbox
10.1 Introduction
10.2 Reading from an image file and writing to an image file
10.3 Fourier domain processing
10.4 Calculation of entropy
10.5 Huffman code
10.6 Arithmetic code
10.7 Segmentation
10.8 Hough transform
10.9 Some common error messages in MATLAB®
Exercises
CH011.pdf
Chapter 11 Video processing
11.1 Introduction
11.2 Extracting frames from a video
11.3 Video compression
11.4 Detection and analysis of motion: optical flows
CH012.pdf
Chapter 12 Solutions to selected exercises
Solutions to Chapter 1 exercises
Solutions to Chapter 2 exercises
Solutions to Chapter 3 exercises
Solutions to Chapter 4 exercises
Solutions to Chapter 5 exercises
Solutions to Chapter 6 exercises
Solutions to Chapter 7 exercises
