Principles of digital image synthesis Volume one Volume one /
Image synthesis, or rendering, is a field of transformation: it changesgeometry and physics into meaningful images. Because the most popularalgorithms frequently change, it is increasingly important for researchersand implementors to have a basic understanding of the principles of imagesynthesis. Fo...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
San Francisco, California :
Morgan Kaufmann Publishers, Inc
1995.
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| Colección: | Morgan Kaufmann series in computer graphics.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009755074106719 |
Tabla de Contenidos:
- Front Cover; Principles of Digital Image Synthesis; Copyright Page; Dedication; Table of Contents; Preface; Summary of Useful Notation; PART I:THE HUMAN VISUAL SYSTEM AND COLOR; INTRODUCTION TO UNIT I; Chapter1. The Human Visual System; 1.1Introduction; 1.2Structure and Optics of the Human Eye; 1.3Spectral and Temporal Aspects of the HVS; 1.4Visual Phenomena; 1.5Depth Perception; 1.6Color Opponency; 1.7Perceptual Color Matching: CIE XYZ Space; 1.8 Illusions; 1.9 Further Reading; 1.10 Exercises; Chapter 2. Color Spaces; 2.1 Perceptually Uniform Color Spaces: L*u*v* and L*a*b*
- 2.2 Other Color Systems2.3 Further Reading; 2.4 Exercises; Chapter 3. Displays; 3.1Introduction; 3.2CRT Displays; 3.3Display Spot Interaction; 3.4Monitors; 3.5RGB Color Space; 3.6Gamut Mapping; 3.7Further Reading; 3.8Exercises; PART II: SIGNAL PROCESSING; INTRODUCTION TO UNIT II; Chapter 4. Signals and Systems; 4.1 Introduction; 4.2 Types of Signals and Systems; 4.3 Notation; 4.4 Some Useful Signals; 4.5 Convolution; 4.6 Two-Dimensional Signals and Systems; 4.7 Further Reading; 4.8 Exercises; Chapter 5.Fourier Transforms; 5.1 Introduction; 5.2 Basis Functions
- 5.3 Representation in Bases of Lower Dimension5.4 Continuous-Time Fourier Representations; 5.5 The Fourier Series; 5.6 The Continuous-Time Fourier Transform; 5.7 Examples; 5.8 Duality; 5.9 Filtering and Convolution; 5.10 The Fourier Transform Table; 5.11 Discrete-Time Fourier Representations; 5.12 Fourier Series and Transforms Summary; 5.13 Convolution Revisited; 5.14 Two-Dimensional Fourier Transforms; 5.15 Higher-Order Transforms; 5.16 The Fast Fourier Transform; 5.17 Further Reading; 5.18 Exercises; Chapter 6. Wavelet Transforms; 6.1 Introduction; 6.2 Short-Time Fourier Transform
- 6.3 Scale and Resolution6.4 The Dilation Equation and the Haar Transform; 6.5 Decomposition and Reconstruction; 6.6 Compression; 6.7 Coefficient Conditions; 6.8 Multiresolution Analysis; 6.9 Wavelets in the Fourier Domain; 6.10 Two-Dimensional Wavelets; 6.11 Further Reading; 6.12 Exercises; Chapter 7. Monte Carlo Integration; 7.1 Introduction; 7.2 Basic Monte Carlo Ideas; 7.3 Confidence; 7.4 Blind Monte Carlo; 7.5 Informed Monte Carlo; 7.6 Adaptive Sampling; 7.7 Other Approaches; 7.8 Summary; 7.9 Further Reading; 7.10 Exercises; Chapter 8. Uniform Sampling and Reconstruction; 8.1 Introduction
- 8.2 Reconstruction8.3 Sampling in Two Dimensions; 8.4 Two-Dimensional Reconstruction; 8.5 Reconstruction in Image Space; 8.6 Supersampling; 8.7 Further Reading; 8.8 Exercises; Chapter 9. Nonuniform Sampling and Reconstruction; 9.1 Introduction; 9.2 Nonuniform Sampling; 9.3Informed Sampling; 9.4Stratified Sampling; 9.5Interlude: The Duality of Aliasing and Noise; 9.6Nonuniform Reconstruction; 9.7Further Reading; 9.8Exercises; Chapter 10.Sampling and Reconstruction Techniques; 10.1Introduction; 10.2General Outline of Signal Estimation; 10.3 Initial Sampling Patterns
- 10.4Uniform and Nonuniform Sampling
