Advances in Imaging And Electron Physics

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ISBN: 9780120147823 | 0120147823
Cover: Hardcover
Copyright: 5/26/2006

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Advances in Imaging and Electron Physics merges two long-running serials--Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. This series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science and digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods used in all these domains.

CONTRIBUTORS

vii

PREFACE

FUTURE CONTRIBUTIONS

Recursive Neural Networks and Their Applications to Image Processing

MONICA BIANCHINI, MARCO MAGGINI, AND LORENZO SARTI

I. Introduction

(8)

A. From Flat to Structural Pattern Recognition

(6)

B. Recursive Neural Networks: Properties and Applications

(2)

II. Recursive Neural Networks

(24)

A. Graphs

(2)

B. Processing DAGs with Recursive Neural Networks

(7)

1. Processing DPAGs

(3)

2. Processing DAGs-LE

(1)

C. Backpropagation Through Structure

(4)

D. Processing Cyclic Graphs

(8)

1. Recursive-Equivalent Transforms

(3)

2. From Cyclic Graphs to Recursive Equivalent Trees

(2)

E. Limitations of the Recursive Neural Network Model

(3)

1. Theoretical Conditions for Collision Avoidance

(2)

III. Graph-Based Representation of Images

(6)

A. Introduction

(1)

B. Segmentation of Images

(3)

C. Region Adjacency Graphs

(2)

D. Multiresolution Trees

(1)

IV. Object Detection in Images

(15)

A. Object Detection Methods

(3)

B. Recursive Neural Networks for Detecting Objects in Images

(20)

1. Learning Environment Setup

(5)

2. Detecting Objects

(7)

References

(8)

Deterministic Learning and an Application in Optimal Control

CRISTIANO CERVELLERA AND MARCO MUSELLI

I. Introduction

(3)

Notation

(1)

II. A Mathematical Framework for the Learning Problem

(4)

III. Statistical Learning

(5)

IV. Deterministic Learning

(16)

A. The Distribution-Free Case

(5)

B. Ensuring a Bounded Variation

(5)

1. Feedforward Neural Networks

(1)

2. Radial Basis Functions

(1)

C. Bounds on the Convergence Rate of the ERM Approach

(2)

D. The Distribution-Dependent Case

(1)

E. The Noisy Case

(2)

V. Deterministic Learning for Optimal Control Problems

(4)

VI. Approximate Dynamic Programming Algorithms

(5)

A. T-SO Problems

(2)

B. infinity-SO Problems

(2)

1. Approximate Value Iteration

(1)

2. Approximate Policy Iteration

(1)

C. Performance Issues

(1)

VII. Deterministic Learning for Dynamic Programming Algorithms

(5)

A. The T-SO Case

(3)

B. The infinity-SO Case

102

(2)

VIII. Experimental Results

104

(10)

A. Approximation of Unknown Functions

104

(3)

B. Multistage Optimization Tests

107

(15)

1. The Inventory Forecasting Model

108

(1)

2. The Water Reservoir Network Model

109

(5)

References

114

(6)

X-Ray Fluorescence Holography

KOUICHI HAYASHI

I. Introduction

120

(2)

II. Theory

122

(16)

A. Theory Using Simple Models

122

(2)

B. Simulation Using Realistic Models

124

(4)

C. Kossel and X-Ray Standing Wave Lines

128

(1)

D. Removal of Twin Images

129

(5)

1. Multiple Energy Method

130

(1)

2. Two Energy Method

130

(3)

3. Complex Holography

133

(1)

E. Polarization Effect of Incident X-Ray

134

(2)

F. Near Field Effect

136

(2)

III. Experiment and Data Processing

138

(21)

A. Experimental Geometries for Normal and Inverse Modes

138

(2)

B. Laboratory XFH Apparatus

140

(3)

C. Fast X-Ray Fluorescence Detection System at SR

143

(2)

D. Details of Data Processing for Obtaining Atomic Images

145

(4)

E. Sample Cooling Effect

149

(1)

F. Inverse Fourier Analysis

150

(9)

1. Theoretical Proof

150

(6)

2. Demonstration by Experimental Holograms

156

(3)

IV. Applications

159

(15)

A. Ultrathin Film

159

(3)

B. Dopants

162

(6)

1. GaAs:Zn

162

(3)

2. Si:Ge

165

(3)

C. Quasicrystal

168

(2)

D. Complex X-Ray Holography

170

(4)

V. Related Methods

174

(6)

A. π XAFS

174

(2)

B. γ-Ray Holography

176

(2)

C. Neutron Holography

178

(2)

VI. Summary and Outlook

180

(1)

References

181

A Taxonomy of Color Image Filtering and Enhancement Solutions

RASTISLAV LUKAC AND KONSTANTINOS N. PLATANIOTIS

I. Introduction

(102)

II. Color Imaging Basics

190

(3)

III. Image Noise

193

(6)

A. Natural Image Noise

193

(1)

B. Noise Modeling

194

(5)

1. Sensor Noise

195

(2)

2. Transmission Noise

197

(2)

IV. Color Image Filtering

199

(45)

A. Noise-Reduction Techniques

202

(1)

1. Order-Statistic Theory for Color Vectors

202

(3)

2. Component-Wise Median Filters

205

(2)

3. Vector Median Filters

207

(5)

4. Vector Directional Filters

212

(3)

5. Selection Weighted Vector Filters

215

(3)

6. Data-Adaptive Vector Filters

218

(2)

7. Adaptive Multichannel Filters Based on Digital Paths

220

(3)

8. Switching Filtering Schemes

223

(3)

9. Similarity Based Vector Filters

226

(2)

10. Adaptive Hybrid Vector Filters

228

(3)

B. Performance Evaluation of the Noise Reduction Filters

231

(3)

1. Objective Evaluation

231

(2)

2. Subjective Evaluation

233

(1)

C. Inpainting Techniques

234

(1)

D. Image Sharpening Techniques

235

(4)

E. Image Zooming Techniques

239

(2)

F. Applications

241

(3)

1. Virtual Restoration of Artworks

241

(2)

2. Television Image Enhancement

243

(1)

V. Edge Detection

244

(13)

A. Scalar Operators

245

(5)

1. Gradient Operators

248

(1)

2. Zero-Crossing-Based Operators

249

(1)

B. Vector Operators

250

(3)

C. Evaluation Criteria

253

(15)

1. Objective Evaluation Approach

254

(1)

2. Subjective Evaluation Approach

255

(2)

VI. Conclusion

257

(1)

References

257

(8)

General Sweep Mathematical Morphology

FRANK Y. SHIH

I. Introduction

265

(3)

II. Theoretical Development of General Sweep Mathematical Morphology

268

(7)

A. Computation of Traditional Morphology

268

(2)

B. General Sweep Mathematical Morphology

270

(3)

C. Properties of Sweep Morphological Operations

273

(2)

III. Blending of Swept Surfaces with Deformations

275

(3)

IV. Image Enhancement

278

(2)

V. Edge Linking

280

(6)

A. Edge Linking Using Sweep Morphology

281

(5)

VI. Shortest Path Planning for Mobile Robot

286

(2)

VII. Geometric Modeling and Sweep Mathematical Morphology

288

(3)

A. Tolerance Expression

289

(2)

B. Sweep Surface Modeling

291

(1)

VIII. Formal Language and Sweep Morphology

291

(1)

IX. Representation Scheme

292

(5)

A. Two-Dimensional Attributes

292

(1)

B. Three-Dimensional Attributes

293

(4)

X. Grammars

297

(3)

A. Two-Dimensional Attributes

298

(1)

B. Three-Dimensional Attributes

298

(2)

XI. Parsing Algorithm

300

(3)

XII. Conclusions

303

(1)

References

303

(3)

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Advances in Imaging And Electron Physics

Summary

Table of Contents

Supplemental Materials