Advances in Imaging and Electron Physics (eBook)

Peter W. Hawkes, Benjamin Kazan, Tom Mulvey (Herausgeber)

eBook Download: PDF

2002 | 1. Auflage
356 Seiten
Elsevier Science (Verlag)
978-0-08-052622-5 (ISBN)

Infos

Advances in Imaging and Electron Physics merges two long-running serials-Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The 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.

Inhalt

Cover 1
Contents 8
Contributors 10
Preface 12
Future Contributions 14
Chapter 1. A Review of Image Segmentation Techniques Integrating Region and Boundary Information 18
I. Introduction 18
II. Embedded Integration 23
III. Postprocessing Integration 34
IV. Summary 48
V. Conclusions and Further Work 52
References 53
Chapter 2. Mirror Corrector for Low-Voltage Electron Microscopes 58
I. Introduction 59
II. General Considerations 61
III. The Spectromicroscope "SMART" 69
IV. Mechanical Design of the Mirror Corrector 89
V. Testing of the Mirror Corrector 101
VI. Conclusion 145
Appendix: Addition of Refractive Powers in the Two-Lens System 147
References 149
Chapter 3. Characterization of Texture in Scanning Electron Microscope Images 152
I. Introduction 153
II. The Variogram as a Surface Characterization Tool 153
III. Variogram Use for Texture Characterization of Digital Images 163
IV. Two Examples of Application in SEM Images 191
V. Conclusions 200
Appendix I: Correlation between Fourier Power Spectrum Maximum and Variogram Characteristic Minimum 200
Appendix II: Theoretical Example to Show the Correlation between the Fourier Power Spectrum Maximum and the Variogram Characteristic Minimum 203
References 206
Chapter 4. Degradation Identification and Model Parameter Estimation in Discontinuity-Adaptive Visual Reconstruction 210
I. Introduction 211
II. Fully Bayesian Approach to Unsupervised Blind Restoration 219
III. The MAP-ML Method 223
IV. MAP Estimation of the Image Field 225
V. ML Estimation of the Degradation Parameters 232
VI. ML Estimation of the Model Parameters 234
VII. The Overall Architecture for the Fully Blind and Unsupervised Restoration 244
VIII. Adaptive Smoothing and Edge Tracking 248
IX. Experimental Results: The Blind Restoration Subcase 255
X. Experimental Results: The Unsupervised Restoration Subcase 264
XI. Experimental Results: The Fully Unsupervised Blind Restoration Case 287
XII. Conclusions 296
References 297
Index 302

Produkt-Details

• Erscheint lt. Verlag: 26.4.2002
• Sprache: englisch
• Themenwelt: Sachbuch/Ratgeber
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Naturwissenschaften ► Physik / Astronomie ► Elektrodynamik
• Themenwelt: Technik ► Bauwesen
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Themenwelt: Technik ► Maschinenbau
• ISBN-10: 0-08-052622-5 / 0080526225
• ISBN-13: 978-0-08-052622-5 / 9780080526225