Advances in Imaging and Electron Physics
Contributors: Kazan, Benjamin; Mulvey, Tom
Publisher: Elsevier
Published: 2002
Place of publication: San Diego
Language: eng
Format: [electronic resource]
Number of pages: 309
ISBN-13: 9780080526225
Subjects: Electrons; Electron optics; Image processing; Imaging system
Description: 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.
Notes: Description based upon print version of record.
Table of contents: title: Front Cover; Advances in Imaging and Electron Physics; Copyright Page; Contents; Contributors; Preface; Future Contributions; Chapter 1. A Review of Image Segmentation Techniques Integrating Region and Boundary Information; I. Introduction; II. Embedded Integration; III. Postprocessing Integration; IV. Summary; V. Conclusions and Further Work; References; Chapter 2. Mirror Corrector for Low-Voltage Electron Microscopes; I. Introduction; II. General Considerations; III. The Spectromicroscope ""SMART""; IV. Mechanical Design of the Mirror Corrector; V. Testing of the Mirror Corrector; title: VI. ConclusionAppendix: Addition of Refractive Powers in the Two-Lens System; References; Chapter 3. Characterization of Texture in Scanning Electron Microscope Images; I. Introduction; II. The Variogram as a Surface Characterization Tool; III. Variogram Use for Texture Characterization of Digital Images; IV. Two Examples of Application in SEM Images; V. Conclusions; Appendix I: Correlation between Fourier Power Spectrum Maximum and Variogram Characteristic Minimum; title: Appendix II: Theoretical Example to Show the Correlation between the Fourier Power Spectrum Maximum and the Variogram Characteristic MinimumReferences; Chapter 4. Degradation Identification and Model Parameter Estimation in Discontinuity-Adaptive Visual Reconstruction; I. Introduction; II. Fully Bayesian Approach to Unsupervised Blind Restoration; III. The MAP-ML Method; IV. MAP Estimation of the Image Field; V. ML Estimation of the Degradation Parameters; VI. ML Estimation of the Model Parameters; VII. The Overall Architecture for the Fully Blind and Unsupervised Restoration; title: VIII. Adaptive Smoothing and Edge TrackingIX. Experimental Results: The Blind Restoration Subcase; X. Experimental Results: The Unsupervised Restoration Subcase; XI. Experimental Results: The Fully Unsupervised Blind Restoration Case; XII. Conclusions; References; Index