Course on Digital Image Processing with MATLAB®

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