Harrison H. Barrett, Kyle Myers

Foundations of Image Science

• Gebundenes Buch

Produktbeschreibung

"Image Science" behandelt die physikalischen Grundlagen von Bildverarbeitungssystemen. Es ist das erste Buch, das eine zusammenhängende Behandlung der Grundlagen, sowie der mathematischen und statistischen Aspekte bietet, die für das Verständnis der Funktion von Bildverarbeitungssystemen erforderlich sind. Autor Harry Barrett ist ein herausragender Forscher auf diesem Gebiet.

Produktdetails

• Wiley Series in Pure and Applied Optics
• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 1584
• Erscheinungstermin: 24. Oktober 2003
• Englisch
• Abmessung: 263mm x 184mm x 61mm
• Gewicht: 2590g
• ISBN-13: 9780471153009
• ISBN-10: 0471153001
• Artikelnr.: 10254915

Autorenporträt

HARRISON H. BARRETT received a BS in physics from Virginia Polytechnic Institute, an MS in Physics from MIT, and a PhD in applied physics from Harvard. Dr. Barrett is a professor in the Optical Sciences Center, the Department of Radiology, and the Program in Applied Mathematics and serves as Director of the Center for Gamma-ray Imaging. The holder of twenty-three U.S. patents, he is the recipient of the IEEE Medical Imaging Scientist Award and a Humboldt Prize and the coauthor, with William Swindell, of Radiological Imaging: The Theory of Image Formation, Detection, and Processing. KYLE J. MYERS received a BS in Mathematics and Physics from Occidental College and an MS and PhD in Optical Sciences from the University of Arizona. Dr. Myers is the Chief of the Medical Imaging and Computer Applications Branch of the Center for Devices and Radiological Health of the U.S. Food and Drug Administration. She is a member of the SPIE, the Optical Society of America, and the Medical Image Perception Society (MIPS), and recently served as cochair of the Medical Image Perception Conference sponsored by MIPS.

Inhaltsangabe

1. VECTORS AND OPERATORS. 1.1 LINEAR VECTOR SPACES. 1.2 TYPES OF OPERATORS.
1.3 HILBERT-SPACE OPERATORS. 1.4 EIGENANALYSIS. 1.5 SINGULAR-VALUE
DECOMPOSITION. 1.6 MOORE-PENROSE PSEUDOINVERSE. 1.7 PSEUDOINVERSES AND
LINEAR EQUATIONS. 1.8 REPRODUCING-KERNEL HILBERT SPACES. 2. THE DIRAC DELTA
AND OTHER GENERALIZED FUNCTIONS. 2.1 THEORY OF DISTRIBUTIONS. 2.2
ONE-DIMENSIONAL DELTA FUNCTION. 2.3 OTHER GENERALIZED FUNCTIONS IN 1D. 2.4
MULTIDIMENSIONAL DELTA FUNCTIONS. 3. FOURIER ANALYSIS. 3.1 SINES, COSINES
AND COMPLEX EXPONENTIALS. 3.2 FOURIER SERIES. 3.3 1D FOURIER TRANSFORM. 3.4
MULTIDIMENSIONAL FOURIER TRANSFORMS. 3.5 SAMPLING THEORY. 3.6 DISCRETE
FOURIER TRANSFORM. 4. SERIES EXPANSIONS AND INTEGRAL TRANSFORMS. 4.1
EXPANSIONS IN ORTHOGONAL FUNCTIONS. 4.2 CLASSICAL INTEGRAL TRANSFORMS. 4.3
FRESNEL INTEGRALS AND TRANSFORMS. 4.4 RADON TRANSFORM. 5. MIXED
REPRESENTATIONS. 5.1 LOCAL SPECTRAL ANALYSIS. 5.2 BILINEAR TRANSFORMS. 5.3
WAVELETS. 6. GROUP THEORY. 6.1 BASIC CONCEPTS. 6.2 SUBGROUPS AND CLASSES.
6.3 GROUP REPRESENTATIONS. 6.4 SOME FINITE GROUPS. 6.5 CONTINUOUS GROUPS.
6.6 GROUPS OF OPERATORS ON A HILBERT SPACE. 6.7 QUANTUM MECHANICS AND IMAGE
SCIENCE. 6.8 FUNCTIONS AND TRANSFORMS ON GROUPS. 7. DETERMINISTIC
DESCRIPTIONS OF IMAGING SYSTEMS. 7.1 OBJECTS AND IMAGES. 7.2 LINEAR
CONTINUOUS-TO-CONTINUOUS SYSTEMS. 7.3 LINEAR CONTINUOUS-TO-DISCRETE
SYSTEMS. 7.4 LINEAR DISCRETE-TO-DISCRETE SYSTEMS. 7.5 NONLINEAR SYSTEMS. 8.
STOCHASTIC DESCRIPTIONS OF OBJECTS AND IMAGES. 8.1 RANDOM VECTORS. 8.2
RANDOM PROCESSES. 8.3 NORMAL RANDOM VECTORS AND PROCESSES. 8.4 STOCHASTIC
MODELS FOR OBJECTS. 8.5 STOCHASTIC MODELS FOR IMAGES. 9. DIFFRACTION THEORY
AND IMAGING. 9.1 WAVE EQUATIONS. 9.2 PLANE WAVES AND SPHERICAL WAVES. 9.3
GREEN'S FUNCTIONS. 9.4 DIFFRACTION BY A PLANAR APERTURE. 9.5 DIFFRACTION IN
THE FREQUENCY DOMAIN. 9.6 IMAGING OF POINT OBJECTS. 9.7 IMAGING OF EXTENDED
PLANAR OBJECTS. 9.8 VOLUME DIFFRACTION AND 3D IMAGING. 10. ENERGY TRANSPORT
AND PHOTONS. 10.1 ELECTROMAGNETIC ENERGY FLOW AND DETECTION. 10.2
RADIOMETRIC QUANTITIES AND UNITS. 10.3 THE BOLTZMANN TRANSPORT EQUATION.
10.4 TRANSPORT THEORY AND IMAGING. 11. POISSON STATISTICS AND PHOTON
COUNTING. 11.1 POISSON RANDOM VARIABLES. 11.2 POISSON RANDOM VECTORS. 11.3
RANDOM POINT PROCESSES. 11.4 RANDOM AMPLIFICATION. 11.5 QUANTUM MECHANICS
OF PHOTON COUNTING. 12. NOISE IN DETECTORS. 12.1 PHOTON NOISE AND SHOT
NOISE IN PHOTODIODES. 12.2 OTHER NOISE MECHANISMS. 12.3 X-RAY AND GAMMA-RAY
DETECTORS. 13. STATISTICAL DECISION THEORY. 13.1 BASIC CONCEPTS. 13.2
CLASSIFICATION TASKS. 13.3 ESTIMATION THEORY. 14. IMAGE QUALITY. 14.1
SURVEY OF APPROACHES. 14.2 HUMAN OBSERVERS AND CLASSIFICATION TASKS. 14.3
MODEL OBSERVERS AND CLASSIFICATION TASKS. 14.4 ESTIMATION TASKS. 14.5
SOURCES OF IMAGES. 15. INVERSE PROBLEMS. 15.1 BASIC CONCEPTS. 15.2 LINEAR
RECONSTRUCTION OPERATORS. 15.3 IMPLICIT ESTIMATES. 15.4 ITERATIVE
ALGORITHMS. 16. PLANAR IMAGING WITH X RAYS AND GAMMA RAYS. 16.1 DIGITAL
RADIOGRAPHY. 16.2 PLANAR NUCLEAR MEDICINE. 17. EMISSION COMPUTED
TOMOGRAPHY. 17.1 FORWARD PROBLEMS. 17.2 INVERSE PROBLEMS. 17.3 NOISE AND
IMAGE QUALITY. 18. SPECKLE. 18.1 BASIC CONCEPTS. 18.2 SPECKLE IN A
NONIMAGING SYSTEMS. 18.3 SPECKLE IN AN IMAGING SYSTEM. 18.4 NOISE AND IMAGE
QUALITY. 18.5 POINT-SCATTERINGMODELSANDNON-GAUSSIANSPECKLE. 18.6 COHERENT
RANGING. 19. IMAGING IN FOURIER SPACE. 19.1 FOURIER MODULATORS. 19.2
INTERFEROMETERS. EPILOGUE. FRONTIERS IN IMAGE SCIENCE. A MATRIX ALGEBRA. B
COMPLEX VARIABLES. C FUNDAMENTALS OF PROBABILITY. Bibliography. Index.