Digital image interpolation in MATLAB® / Chi-Wah Kok and Wing-Shan Tam.

Format:

Book

Author/Creator:

Kok, Chi-Wah, author.

Tam, Wing-Shan, author.

Series:

THEi Wiley ebooks.

Language:

English

Subjects (All):

Image processing--Digital techniques--Data processing.

Image processing.

Interpolation.

MATLAB.

Physical Description:

1 online resource (339 pages)

Edition:

First edition

Place of Publication:

Hoboken, New Jersey : Wiley : IEEE Press, 2019.

System Details:

Access using campus network via VPN at home (THEi Users Only).

text file

Summary:

This book provides a comprehensive study in digital image interpolation with theoretical, analytical and Matlab® implementation. It includes all historically and practically important interpolation algorithms, accompanied with Matlab® source code on a website, which will assist readers to learn and understand the implementation details of each presented interpolation algorithm. Furthermore, sections in fundamental signal processing theories and image quality models are also included. The authors intend for the book to help readers develop a thorough consideration of the design of image interpolation algorithms and applications for their future research in the field of digital image processing. Introduces a wide range of traditional and advanced image interpolation methods concisely and provides thorough treatment of theoretical foundations Discusses in detail the assumptions and limitations of presented algorithms Investigates a variety of interpolation and implementation methods including transform domain, edge-directed, wavelet and scale-space, and fractal based methods Features simulation results for comparative analysis, summaries and computational and analytical exercises at the end of each chapter Digital Image Interpolation in Matlab® is an excellent guide for researchers and engineers working in digital imaging and digital video technologies. Graduate students studying digital image processing will also benefit from this practical reference text.

Contents:

Cover

Title Page

Copyright

Contents

About the Authors

Preface

Acknowledgments

Nomenclature

Abbreviations

About the Companion Website

Chapter 1 Signal Sampling

1.1 Sampling and Bandlimited Signal

1.2 Unitary Transform

1.2.1 Discrete Fourier Transform

1.3 Quantization

1.3.1 Quantization and Sampling Interaction

1.4 Sampled Function Approximation: Fitting and Interpolation

1.4.1 Zero‐Order Hold (ZOH)

1.4.2 First‐Order Hold (FOH)

1.4.3 Digital Interpolation

1.5 Book Organization

1.6 Exercises

Chapter 2 Digital Image

2.1 Digital Imaging in MATLAB

2.2 Current Pixel and Neighboring Pixels

2.3 Frequency Domain

2.3.1 Transform Kernel

2.4 2D Filtering

2.4.1 Boundary Extension and Cropping

2.4.1.1 Constant Extension

2.4.1.2 Periodic Extension

2.4.1.3 Symmetric Extension

2.4.1.4 Infinite Extension

2.4.1.5 Cropping

2.5 Edge Extraction

2.5.1 First‐Order Derivative Edge Detection Operators

2.5.1.1 Sobel Operator

2.5.2 Second‐Order Derivative and Zero‐Crossing Edge Detector

2.5.2.1 Laplacian Operator

2.5.2.2 Gaussian Smoothing

2.6 Geometric Transformation

2.6.1 Translation

2.6.2 Reflection

2.6.3 Scaling

2.6.4 Rotation

2.6.5 Affine Transformation

2.7 Resize an Image

2.7.1 Interpolation

2.7.2 Decimation

2.7.2.1 Direct Subsampling

2.7.2.2 Sinc Filter

2.7.2.3 Block Averaging

2.7.3 Built‐in Image Resizing Function in MATLAB

2.8 Color Image

2.8.1 Color Filter Array and Demosaicing

2.8.2 Perceptual Color Space

2.9 Noise

2.9.1 Rank Order Filtering

2.9.2 Smoothing Filtering

2.10 Summary

2.11 Exercises

Chapter 3 Image Quality

3.1 Image Features and Artifacts

3.1.1 Aliasing (Jaggy)

3.1.2 Smoothing (Blurring)

3.1.3 Edge Halo

3.1.4 Ringing

3.1.5 Blocking.

3.2 Objective Quality Measure

3.2.1 Mean Squares Error

3.2.2 Peak Signal‐to‐Noise Ratio

3.2.3 Edge PSNR

3.3 Structural Similarity

3.3.1 Luminance

3.3.2 Contrast

3.3.3 Structural

3.3.4 Sensitivity of SSIM

3.3.4.1 K1 Sensitivity

3.3.4.2 K2 Sensitivity

3.4 Summary

3.5 Exercises

Chapter 4 Nonadaptive Interpolation

4.1 Image Interpolation: Overture

4.1.1 Interpolation Kernel Characteristics

4.1.2 Nearest Neighbor

4.1.3 Bilinear

4.1.4 Bicubic

4.2 Frequency Domain Analysis

4.3 Mystery of Order

4.4 Application: Affine Transformation

4.4.1 Structural Integrity

4.5 Summary

4.6 Exercises

Chapter 5 Transform Domain

5.1 DFT Zero Padding Interpolation

5.1.1 Implementation

5.2 Discrete Cosine Transform

5.2.1 DCT Zero Padding Interpolation

5.3 DCT Zero Padding Image Interpolation

5.3.1 Blocked Transform

5.3.2 Block‐Based DCT Zero Padding Interpolation

5.3.2.1 Does Kernel Size Matter

5.4 Overlapping

5.5 Multi‐Kernels

5.5.1 Extendible Inverse DCT

5.6 Iterative Error Correction

5.7 Summary

5.8 Exercises

Chapter 6 Wavelet

6.1 Wavelet Analysis

6.1.1 Perfect Reconstruction

6.1.2 Multi‐resolution Analysis

6.1.3 2D Wavelet Transform

6.2 Wavelet Image Interpolation

6.2.1 Zero Padding

6.2.2 Multi‐resolution Subband Image Estimation

6.2.3 Hölder Regularity

6.2.3.1 Local Regularity‐Preserving Problems

6.3 Cycle Spinning

6.3.1 Zero Padding (WZP‐CS)

6.3.2 High Frequency Subband Estimation (WLR‐CS)

6.4 Error Correction

6.5 Which Wavelets to Use

6.6 Summary

6.7 Exercises

Chapter 7 Edge‐Directed Interpolation

7.1 Explicit Edge‐Directed Interpolation

7.2 Implicit Edge‐Directed Interpolation

7.2.1 Canny Edge Interpolation (CEI)

7.2.2 Edge‐Based Line Averaging (ELA).

7.2.3 Directional‐Orientation Interpolation (DOI)

7.2.4 Error‐Amended Sharp Edge (EASE)

7.3 Summary

7.4 Exercises

Chapter 8 Covariance‐Based Interpolation

8.1 Modeling of Image Features

8.2 Interpolation by Autoregression

8.3 New Edge‐Directed Interpolation (NEDI)

8.3.1 Type 0 Estimation

8.3.2 Type 1 Estimation

8.3.3 Type 2 Estimation

8.3.4 Pixel Intensity Correction

8.3.5 MATLAB Implementation

8.4 Boundary Extension

8.5 Threshold Selection

8.6 Error Propagation Mitigation

8.7 Covariance Window Adaptation

8.7.1 Prediction Window Adaptation

8.7.2 Mean Covariance Window Adaptation

8.7.3 Enhanced Modified Edge‐Directed Interpolation (EMEDI)

8.8 Iterative Covariance Correction

8.8.1 iMEDI Implementation

8.9 Summary

8.10 Exercises

Chapter 9 Partitioned Fractal Interpolation

9.1 Iterated Function System

9.1.1 Banach Fixed‐Point Theorem

9.2 Partitioned Iterative Function System

9.3 Encoding

9.3.1 Range Block Partition

9.3.2 Domain Block Partition

9.3.3 Codebook Generation

9.3.4 Grayscale Scaling

9.3.5 Fractal Encoding Implementation

9.4 Decoding

9.4.1 Does Size Matter

9.5 Decoding with Interpolation

9.5.1 From Fitting to Interpolation

9.6 Overlapping

9.7 Summary

9.8 Exercises

Appendix MATLAB Functions List

Bibliography

Index

Supplemental Images

EULA.

Notes:

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9781119119623

9781119119647

1119119642

9781119119630

1119119634

OCLC:

1080997486