An essential reference for optical sensor system design <p> This is the first text to present an integrated view of the optical and mathematical analysis tools necessary to understand computational optical system design. It presents the foundations of computational optical sensor design with a
Optical imaging and spectroscopy
β Scribed by David J Brady
- Publisher
- Wiley
- Year
- 2008
- Tongue
- English
- Leaves
- 518
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Content: Preface. Acknowledgments. 1. Past, present and future. 1.1 Three revolutions. 1.2 Computational imaging. 1.3 Overview. 1.4 The fourth revolution. Problems. 2. Geometric imaging. 2.1 Visibility. 2.2 Optical elements. 2.3 Focal imaging. 2.4 Imaging systems. 2.5 Pinhole and coded aperture imaging. 2.6 Projection tomography. 2.7 Reference structure tomography. Problems. 3. Analysis. 3.1 Analytical tools. 3.2 Fields and transformations. 3.3 Fourier analysis. 3.4 Transfer functions and filters. 3.5 The Fresnel transformation. 3.6 The Whittaker-Shannon sampling theorem. 3.7 Discrete analysis of linear transformations. 3.8 Multiscale sampling. 3.9 B-splines. 3.10 Wavelets. Problems. 4. Wave imaging. 4.1 Waves and fields. 4.2 Wave model for optical fields. 4.3 Wave propagation. 4.4 Diffraction. 4.5 Wave analysis of optical elements. 4.6 Wave propagation through thin lenses. 4.7 Fourier analysis of wave imaging. 4.8 Holography. Problems. 5. Detection. 5.1 The Optoelectronic interface. 5.2 Quantum mechanics of optical detection. 5.3 Optoelectronic detectors. 5.3.1 Photoconductive detectors. 5.3.2 Photodiodes. 5.4 Physical characteristics of optical detectors. 5.5 Noise. 5.6 Charge coupled devices. 5.7 Active pixel sensors. 5.8 Infrared focal plane arrays. Problems. 6. Coherence imaging. 6.1 Coherence and spectral fields. 6.2 Coherence propagation. 6.3 Measuring coherence. 6.4 Fourier analysis of coherence imaging. 6.5 Optical coherence tomography. 6.6 Modal analysis. 6.7 Radiometry. Problems. 7. Sampling. 7.1 Samples and pixels. 7.2 Image plane sampling on electronic detector arrays. 7.3 Color imaging. 7.4 Practical sampling models. 7.5 Generalized sampling. Problems. 8. Coding and inverse problems. 8.1 Coding taxonomy. 8.2 Pixel coding. 8.3 Convolutional coding. 8.4 Implicit coding. 8.5 Inverse problems. Problems. 9. Spectroscopy. 9.1 Spectral measurements. 9.2 Spatially dispersive spectroscopy. 9.3 Coded aperture spectroscopy. 9.4 Interferometric Spectroscopy. 9.5 Resonant spectroscopy. 9.6 Spectroscopic filters. 9.7 Tunable filters. 9.8 2D spectroscopy. Problems. 10. Computational imaging. 10.1 Imaging systems. 10.2 Depth of field. 10.3 Resolution. 10.4 Multiple aperture imaging. 10.5 Generalized sampling revisited. 10.6 Spectral imaging. Problems. References.
π SIMILAR VOLUMES
Presents the latest developments in detecting and probing single entities. A thorough yet concise survey of current methods and their applications are included.
Presents the latest developments in detecting and probing single entities. A thorough yet concise survey of current methods and their applications are included.
<p>This volume of Methods in Enzymology is the first of 3 parts looking at current methodology for the imaging and spectroscopic analysis of live cells. The chapters provide hints and tricks not available in primary research publications. It is an invaluable resource for academics, researchers and s
This is an interdisciplinary book that presents the applications of novel laser spectroscopy and imaging techniques for the detection of cancers recently developed by some of the world's most renown researchers. The book consists of three parts and a total of 16 chapters. Each chapter is written by