A course on digital image processing with MATLAB / P.K. Thiruvikraman.

Format:

Book

Author/Creator:

Thiruvikraman, P. K., author.

Contributor:

Institute of Physics (Great Britain), publisher.

Series:

IOP ebooks. 2020 collection.

IOP ebooks. [2020 collection]

Language:

English

Subjects (All):

MATLAB.

Image processing--Digital techniques.

Image processing.

Physical Description:

1 online resource (various pagings) : illustrations (some color).

Place of Publication:

Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2020]

System Details:

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.

text file

Biography/History:

P.K. Thiruvikraman is currently Professor of Physics at Birla Institute of Technology and Science, Pilani, Hyderabad Campus. He has nearly two decades of experience in teaching courses from many areas of Physics apart from Digital Image Processing. The author has a PhD in Physics from Mangalore University and a Masters degree in physics from Indian Institute of Technology, Madras. During his teaching career he has come to realize that most subjects which are typically offered by different departments are intimately interrelated. He tries to convey this to students in his lectures by quoting examples from different areas of science and technology. An avid reader of both fiction and non-fiction and a sports and movie enthusiast, he tries to use these also to enliven his classes.

Summary:

Concentrating on the principles and techniques of image processing, this book provides an in-depth presentation of key topics, including many techniques not included in introductory texts. Practical implementation of the various image processing algorithms is an important step in learning the subject, and computer packages such as MATLAB facilitate this without the need to learn more complex programming languages. Whilst two chapters are devoted to the MATLAB programming environment and the image processing toolbox, the use of image processing algorithms using MATLAB is emphasised throughout the book, and every chapter is accompanied by a collection of exercises and programming assignments. Including coverage of colour and video image processing as well as object recognition, the book is augmented with supplementary MATLAB code and hints and solutions to problems are also provided.

Contents:

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

2. Image enhancement in the spatial domain

2.1. Enhancement of contrast

2.2. Gray level transformations

2.3. Bit plane slicing

2.4. Histogram processing

2.5. Filtering in the spatial domain

2.6. Sharpening in the spatial domain

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

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

4.10. Reducing interpixel redundancy : run-length coding

4.11. LZW coding

4.12. Arithmetic coding

4.13. Transform coding

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

5.5. Thresholding

5.6. A global view of image analysis and pattern recognition

5.7. Representation of objects

5.8. Texture

5.9. Skeletonization or medial axis transformation (MAT)

5.10. Principal component analysis (PCA)

5.11. Pattern recognition

6. Image restoration

6.1. Analyzing motion blur

6.2. Inverse filtering

6.3. Noise

6.4. Removal of noise by morphological operations

6.5. Alternative method for extracting and labeling connected components

6.6. Image reconstruction from projections

7. Wavelets

7.1. Wavelets versus the Fourier transform

7.2. The Haar wavelet transform

7.3. An alternative view of wavelets

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

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

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

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

12. Solutions to selected exercises.

Notes:

"Version: 20191101"--Title page verso.

Title from PDF title page (viewed on December 9, 2019).

Other Format:

Print version:

ISBN:

9780750326049

9780750326032

OCLC:

1130295066

Access Restriction:

Restricted for use by site license.