Preface
. -- 1 Introduction 1
. -- 1.1 Images And Pictures
. -- 1.2 What Is Image Processing?
. -- 1.3 Image Acquisition And Sampling
. -- 1.4 Images And Digital Images
. -- 1.5 Some Applications
. -- 1.6 Image Processing Operations
. -- 1.7 An Image Processing Task
. -- 1.8 Types Of Digital Images
. -- 1.9 Image File Sizes
. -- 1.10 Image Perception
. -- Exercises
. -- 2 Images Files And File Types
. -- 2.1 Opening And Viewing Grayscale Images
. -- 2.2 Rgb Images
. -- 2.3 Indexed Color Images
. -- 2.4 Numeric Types And Conversions
. -- 2.5 Image Files And Formats
. -- 2.6 Programs
. -- Exercises
. -- 3 Image Display
. -- 3.1 Introduction
. -- 3.2 The Imshow Function
. -- 3.3 Bit Planes
. -- 3.4 Spatial Resolution
. -- 3.5 Quantization And Dithering
. -- 3.6. Programs
. -- Exercises
. -- 4 Point Processing
. -- 4.1 Introduction
. -- 4.2 Arithmetic Operations
. -- 4.3 Histograms
. -- 4.4 Lookup Tables
. -- Exercises
. -- 5 Neighborhood Processing
. -- 5.1 In
. -- 5.2 Notation 5.3 Filtering In Matlab And Octave 5.4 Filtering In Python 5.5 Frequencies; Low And High Pass Filters 5.6 Gaussian Filters 5.7 Edge Sharpening 5.8 Non-Linear Filters 5.9 Edge-Preserving Blurring Filters 5.10 Region Of Interest Processing 5.11 Programs Exercises 6 Image Geometry 6.1 Interpolation Of Data 6.2 Image Interpolation 6.3 General Interpolation 6.4 Enlargement By Spatial Filtering 6.5 Scaling Smaller 6.6 Rotation 6.7 Correcting Image Distortion Exercises 7 The Fourier Transform 7.1 Introduction 7.2 Background 7.3 The One-Dimensional Discrete Fourier Transform 7.4 Properties Of The One-Dimensional Dft 7.5 The Two-Dimensional Dft 7.6 Experimenting With Fourier Transforms 7.7 Fourier Transforms Of Synthetic Images 7.8 Filtering In The Frequency Domain 7.9 Homomorphic Filtering 7.10 Programs Exercises 8 Image Restoration 193 8.1 Introduction 8.2 Noise 8.3 Cleaning Salt And Pepper Noise 8.4 Cleaning Gaussian Noise 8.5 Removal Of Periodic Noise 8.6 Inverse 8.7 Wiener Filtering Exercises 9 Image Segmentation 9.1 Introduction 9.2 Thresholding 9.3 Applications Of Thresholding 9.4 Choosing An Appropriate Threshold Value 9.5 Adaptive Thresholding 9.6 Edge Detection 9.7 Derivatives And Edges 9.8 Second Derivatives 9.9 The Canny Edge Detector 9.10 Corner Detection
. -- 9.11 The Hough And Radon Transforms Exercises 10 Mathematical Morphology 10.1 Introduction 10.2 Basic Ideas 10.3 Dilation And Erosion 10.4 Opening And Closing 10.5 The Hit-Or-Miss Transform 10.6 Some Morphological Algorithms 10.7 a Note On The Bwmorph Function In Matlab And Octave 10.8 Grayscale Morphology 10.9 Applications Of Grayscale Morphology 10.10 Programs Exercises 11 Image Topology 11.1 Introduction 11.2 Neighbors And Adjacency 11.3 Paths And Components 11.4 Equivalence Relations 11.5 Component Labeling 11.6 Lookup Tables 11.7 Distances And Metrics 11.8 Skeletonization 11.9 Programs Exercises 12 Shapes And Boundaries 12.1 Introduction 12.2 Chain Codes And Shape Numbers 12.3 Fourier Descriptors Exercises 13 Color Processing 13.1 What Is Color? 13.2 Color Models 13.3 Manipulating Color Images 13.4 Pseudocoloring 13.5 Processing Of Color Images 13.6 Programs Exercises 14 Image Coding And Compression 14.1 Lossless And Lossy Compression 14.2 Huffman Coding 14.3 Run Length Encoding 14.4 Dictionary Coding: Lzw Compression 14.5 The Jpeg Algorithm 14.6 Programs Exercises 15 Wavelets 15.1 Waves And Wavelets 15.2 a Simple Wavelet: The Haar Wavelet 15.3 Wavelets And Images 15.4 The Daubechies Wavelets 15.5 Image Compression Using Wavelets
. -- 15.6 High Pass Filtering Using Wavelets 15.7 Denoising Using Wavelets Exercises 16 Special Effects 16.1 Polar Coordinates 16.2 Ripple Effects 16.3 General Distortion Effects 16.4 Pixel Effects 16.5 Color Images Exercises a Introduction To Matlab And Octave A.1 Introduction A.2 Basic Use A.3 Variables And The Workspace A.4 Dealing With Matrices A.5 Plots A.6 Online Help A.7 Programming Exercises B Introduction To Python 505 B.1 Basic Use B.2 Arrays B.3 Graphics