Image Super-Resolution and Applications

Image Super-Resolution and Applications

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Features

  • Covers polynomial image interpolation, adaptive polynomial image interpolation, and a neural modeling method for polynomial image interpolation
  • Details techniques for color image interpolation
  • Analyzes image interpolation for pattern recognition and explains image interpolation as an inverse problem
  • Discusses image registration methodologies and image fusion and its application in image super resolution
  • Includes MATLAB programs

Summary

This book is devoted to the issue of image super-resolution—obtaining high-resolution images from single or multiple low-resolution images. Although there are numerous algorithms available for image interpolation and super-resolution, there’s been a need for a book that establishes a common thread between the two processes. Filling this need, Image Super-Resolution and Applications presents image interpolation as a building block in the super-resolution reconstruction process.

Instead of approaching image interpolation as either a polynomial-based problem or an inverse problem, this book breaks the mold and compares and contrasts the two approaches. It presents two directions for image super-resolution: super-resolution with a priori information and blind super-resolution reconstruction of images. It also devotes chapters to the two complementary steps used to obtain high-resolution images: image registration and image fusion.

  • Details techniques for color image interpolation and interpolation for pattern recognition
  • Analyzes image interpolation as an inverse problem
  • Presents image registration methodologies
  • Considers image fusion and its application in image super resolution
  • Includes simulation experiments along with the required MATLAB® code

Supplying complete coverage of image-super resolution and its applications, the book illustrates applications for image interpolation and super-resolution in medical and satellite image processing. It uses MATLAB® programs to present various techniques, including polynomial image interpolation and adaptive polynomial image interpolation. MATLAB codes for most of the simulation experiments supplied in the book are included in the appendix.

Table of Contents

Introduction
Image Interpolation
Image Super-Resolution

Polynomial Image Interpolation
Introduction
Classical Image Interpolation
B-Spline Image Interpolation
     Polynomial Splines
     B-Spline Variants
          Nearest Neighbor Interpolation
          Linear Interpolation
          Cubic Spline Interpolation
          Digital Filter Implementation of B-Spline Interpolation
O-MOMS Interpolation
Keys’ (Bicubic) Interpolation
Artifacts of Polynomial Image Interpolation
     Ringing
     Aliasing
     Blocking
     Blurring

Adaptive Polynomial Image Interpolation
Introduction
Low-Resolution Image Degradation Model
Linear Space-Invariant Image Interpolation
Warped-Distance Image Interpolation
Weighted Image Interpolation
Iterative Image Interpolation
Simulation Examples

Neural Modeling of Polynomial Image Interpolation
Introduction
Fundamentals of ANNs
     Cells
          Layers
     Arcs
     Weights
     Activation Rules
     Activation Functions
          Identity Function
          Step Function
          Sigmoid Function
          Piecewise-Linear Function
          Arc Tangent Function
          Hyperbolic Tangent Function
     Outputs
     Learning Rules
          Supervised Learning
          Unsupervised Learning
Neural Network Structures
     Multi-Layer Perceptrons
     Radial Basis Function Networks
     Wavelet Neural Network
     Recurrent ANNs
Training Algorithm
Neural Image Interpolation
Simulation Examples

Color Image Interpolation
Introduction
Color Filter Arrays
     White Balance
     Bayer Interpolation
Linear Interpolation with Laplacian Second Order Correction
Adaptive Color Image Interpolation

Image Interpolation for Pattern Recognition
Introduction
Cepstral Pattern Recognition
Feature Extraction
     Extraction of MFCCs
          Framing and Windowing
          Discrete Fourier Transform
          Mel Filter Bank
          Discrete Cosine Transform
     Polynomial Coefficients
Feature Extraction from Discrete Transforms
     Discrete Wavelet Transform
     Discrete Cosine Transform
     Discrete Sine Transform
Feature Matching Using ANNs
Simulation Examples

Image Interpolation as Inverse Problem
Introduction
Adaptive Least-Squares Image Interpolation
LMMSE Image Interpolation
Maximum Entropy Image Interpolation
Regularized Image Interpolation
Simulation Examples
Interpolation of Infrared Images

Image Registration
Introduction
Applications of Image Registration
     Different Viewpoints (Multi-View Analysis)
     Different Times (Multi-Temporal Analysis)
     Different Sensors (Multi-Modal Analysis)
     Scene-to-Model Registration
Steps of Image Registration
     Feature Detection Step
     Feature Matching Step
          Area-Based Methods
          Feature-Based Methods
     Transform Model Estimation
          Global Mapping Models
          Local Mapping Models
     Image Resampling and Transformation
Evaluation of Image Registration Accuracy

Image Fusion
Introduction
Objectives of Image Fusion
Implementation of Image Fusion
Pixel Level Image Fusion
Principal Component Analysis Fusion
Wavelet Fusion
     DWT Fusion
     DWFT Fusion
Curvelet Fusion
     Sub-Band Filtering
     Tiling
     Ridgelet Transform
IHS Fusion
High-Pass Filter Fusion
Gram–Schmidt Fusion
Fusion of Satellite Images
Fusion of MR and CT Images

Super-Resolution with a Priori Information
Introduction
Multiple Observation LR Degradation Model
Wavelet-Based Image Super-Resolution
Simplified Multi-Channel Degradation Model
Multi-Channel Image Restoration
     Multi-Channel LMMSE Restoration
     Multi-Channel Maximum Entropy Restoration
     Multi-Channel Regularized Restoration
Simulation Examples

Blind Super-Resolution Reconstruction of Images
Introduction
Problem Formulation
Two-Dimensional GCD Algorithm
4 Blind Super-Resolution Reconstruction Approach
Simulation Examples

Appendix A: Discrete B-Splines
Appendix B: Toeplitz-to-Circulant Approximations
Appendix C: Newton’s Method
Appendix D: MATLAB® Codes

References
Index

Author Bio(s)

Fathi E. Abd El-Samie, earned his BSc (Hons) in 1998, MSc in 2001, and PhD in 2005 all from Menoufia University, Menouf, Egypt. Since 2005, he has been a teaching staff member with the Department of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University. He is a coauthor of 160 papers published in international conference proceedings and journals.

His current research areas of interest include image enhancement, image restoration, image interpolation, super-resolution reconstruction of images, data hiding, multimedia communications, medical image processing, optical signal processing, and digital communications. Dr. Abd El-Samie was a recipient of the Most Cited Paper Award from the Digital Signal Processing journal in 2008.

Mohiy M. Hadhoud PhD, received his BSc (Hons) in 1976 and MSc in 1981 from the Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt, and his PhD from Southampton University in 1987. He joined the teaching staff of the Department of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt from 1981 to 2001. He is currently a professor in the Department of Information Technology, Faculty of Computers and Information, Menoufia University, Shiben El-Kom.

Dr. Hadhoud has published more than 100 scientific papers in national and international conferences and journals. His current research areas of interest include adaptive signal and image processing techniques, image enhancement, image restoration, super-resolution reconstruction of images, data hiding and image coloring.

Said El-Khamy PhD, received his PhD from the University of Massachusetts, Amherst, in 1971. He is currently a professor emeritus, Department of Electrical Engineering, Faculty of Engineering, Alexandria University, Alexandria, Egypt. He served as the Chairman of the Electrical Engineering Department from September 2000 to September 2003. While on academic leaves, he taught in Saudi Arabia, Iraq, Lebanon, and the Arab Academy for Science and Technology (AAST).

His current research areas of interest include mobile and personal communications, wave propagation in different media, smart antenna arrays, image processing and watermarking, modern signal processing techniques including neural networks, wavelets, genetic algorithms, fractals, HOS and fuzzy algorithms, and their applications in image processing, communication systems, antenna design and wave propagation problems. He has published more than 300 scientific papers in national and international conferences and journals.

Dr. El-Khamy participated in the organization of many local and international conferences including the yearly series of NRSC (URSI), ISCC 1995, ISCC 1997, ISSPIT 2000, and MELECON 2002. He also chaired technical sessions in many local and international conferences including, ISSSTA 1996, Mainz, Germany, Sept. 1966; IGARSS’98, Seattle, Washington, USA, July 1998 and AP-S’99, Orlando, Florida, USA, July 1999. He is the chairman of the National Radio Science conferences (NRSC2011 and NRSC2012).

He has earned many national and international research awards among which are the Alexandria University Research Award, 1979, the IEEE, R.W.P. King best paper award of the Antennas and Propagation Society of IEEE, in 1980, the Egypt’s National Engineering Research award (twice) in 1980 and 1989, the Egypt’s State Science & Art Decoration of the first class, 1981, the A. Schoman’s - Jordan’s award for Engineering Research in 1982, the Egypt’s state Excellence Decoration of the first class in 1995. He was selected as the National Communication Personality for 2002. Recently, he received three major prestigious national prizes, namely, the State Scientific Excellence award in Engineering Sciences for 2002, the Alexandria University Appreciation of Engineering Sciences for 2004 and finally, the State Appreciation Award of Engineering Sciences for 2004 and the IEEE Region 8 Volunteer Award for 2011.

Prof. El-Khamy is a Fellow Member of the IEEE since 1999 and he obtained the IEEE Life Fellow certificate in 2010. He is a Fellow of the Electromagnetic Academy and a member of Tau Beta Pi, Eta Kappa Nu and Sigma Xi. He is the founder and former chairman of the Alexandria/Egypt IEEE Subsection. Currently, he is the president of Egypt’s National URSI Committee (NRSC) and Egypt’s National URSI Correspondent for Commission C.