E-Book, Englisch, 502 Seiten
El-Samie / Hadhoud / El-Khamy Image Super-Resolution and Applications
Erscheinungsjahr 2013
ISBN: 978-1-4665-5797-0
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
E-Book, Englisch, 502 Seiten
ISBN: 978-1-4665-5797-0
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
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.
Zielgruppe
Students and researchers studying image super resolution.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
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




