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Book Description

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. 

Table of Contents

  1. Cover
  2. Dedication
  3. About the Authors
  4. Preface
  5. Acknowledgments
  6. Nomenclature
  7. Abbreviations
  8. About the Companion Website
  9. 1 Signal Sampling
    1. 1.1 Sampling and Bandlimited Signal
    2. 1.2 Unitary Transform
    3. 1.3 Quantization
    4. 1.4 Sampled Function Approximation: Fitting and Interpolation
    5. 1.5 Book Organization
    6. 1.6 Exercises
  10. 2 Digital Image
    1. 2.1 Digital Imaging in MATLAB
    2. 2.2 Current Pixel and Neighboring Pixels
    3. 2.3 Frequency Domain
    4. 2.4 2D Filtering
    5. 2.5 Edge Extraction
    6. 2.6 Geometric Transformation
    7. 2.7 Resize an Image
    8. 2.8 Color Image
    9. 2.9 Noise
    10. 2.10 Summary
    11. 2.11 Exercises
  11. 3 Image Quality
    1. 3.1 Image Features and Artifacts
    2. 3.2 Objective Quality Measure
    3. 3.3 Structural Similarity
    4. 3.4 Summary
    5. 3.5 Exercises
  12. 4 Nonadaptive Interpolation
    1. 4.1 Image Interpolation: Overture
    2. 4.2 Frequency Domain Analysis
    3. 4.3 Mystery of Order
    4. 4.4 Application: Affine Transformation
    5. 4.5 Summary
    6. 4.6 Exercises
  13. 5 Transform Domain
    1. 5.1 DFT Zero Padding Interpolation
    2. 5.2 Discrete Cosine Transform
    3. 5.3 DCT Zero Padding Image Interpolation
    4. 5.4 Overlapping
    5. 5.5 Multi‐Kernels
    6. 5.6 Iterative Error Correction
    7. 5.7 Summary
    8. 5.8 Exercises
  14. 6 Wavelet
    1. 6.1 Wavelet Analysis
    2. 6.2 Wavelet Image Interpolation
    3. 6.3 Cycle Spinning
    4. 6.4 Error Correction
    5. 6.5 Which Wavelets to Use
    6. 6.6 Summary
    7. 6.7 Exercises
  15. 7 Edge‐Directed Interpolation
    1. 7.1 Explicit Edge‐Directed Interpolation
    2. 7.2 Implicit Edge‐Directed Interpolation
    3. 7.3 Summary
    4. 7.4 Exercises
  16. 8 Covariance‐Based Interpolation
    1. 8.1 Modeling of Image Features
    2. 8.2 Interpolation by Autoregression
    3. 8.3 New Edge‐Directed Interpolation (NEDI)
    4. 8.4 Boundary Extension
    5. 8.5 Threshold Selection
    6. 8.6 Error Propagation Mitigation
    7. 8.7 Covariance Window Adaptation
    8. 8.8 Iterative Covariance Correction
    9. 8.9 Summary
    10. 8.10 Exercises
  17. 9 Partitioned Fractal Interpolation
    1. 9.1 Iterated Function System
    2. 9.2 Partitioned Iterative Function System
    3. 9.3 Encoding
    4. 9.4 Decoding
    5. 9.5 Decoding with Interpolation
    6. 9.6 Overlapping
    7. 9.7 Summary
    8. 9.8 Exercises
  18. AppendixMATLAB Functions List
  19. Bibliography
  20. Index
  21. End User License Agreement
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