A Course on Digital Image Processing with MATLAB® / P. K. Thiruvikraman.

Format:

Book

Author/Creator:

Thiruvikraman, P. K., author.

Series:

IOP Ebooks Series

Language:

English

Subjects (All):

Image processing.

Image processing--Digital techniques.

MATLAB.

Physical Description:

1 online resource (273 pages)

Edition:

First edition.

Place of Publication:

Bristol, England : IOP Publishing, [2020]

Summary:

A Course on Digital Image Processing with MATLAB® 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 code, and hints and solutions to problems are also provided.

Contents:

Intro

Preface

Acknowledgments

Author biography

P K Thiruvikraman

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

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:

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

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

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

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

Chapter 7 Wavelets

7.1 Wavelets versus the Fourier transform

7.2 The Haar wavelet transform

7.3 An alternative view of wavelets

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

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

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®

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

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.

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

ISBN:

9780750341776

0750341777

OCLC:

1129600390