| Description |
1 online resource : text file, PDF |
| Contents |
Cover; Half Title; Title Page; Copyright Page; Dedication; Table of Contents; List of Figures; List of color Figures; List of Tables; Preface; 1: Introduction; 1.1 Intrinsic Physical Models for Computer Vision; 1.2 A Physical Approach to Color Image Understanding; 1.3 Preview of Results; 1.4 Outline; 2: A Physical Reflection Model; 2.1 The Physics of Light Reflection; 2.2 The Dichromatic Reflection Model; 2.3 Object Shape and Spectral Variation; 2.4 Dimensionality of the Measurement Space; 2.5 Material Classes; 2.6 Summary; 3: A Sensor Model; 3.1 Spectral Integration |
|
3.2 Limited Dynamic Range3.3 Color Balancing and Spectral Linearization; 3.4 Chromatic Aberration; 3.5 Examples: Color Clusters from Real Color Images; 3.6 Summary; 4: Color Image Segmentation; 4.1 Color Image Analysis Guided by the Dichromatic Reflection Model; 4.2 Generating Initial Estimates for Color Clusters; 4.3 Generating Linear Hypotheses; 4.4 Exploiting Linear Hypotheses; 4.5 Generating Planar Hypotheses; 4.6 Exploiting Planar Hypotheses; 4.7 Accounting for Camera Limitations; 4.8 Optical Effects Beyond the Scope; 4.9 Summary; 5: Separating Pixels into Their Reflection Components |
|
5.1 Determining Body and Surface Reflection Vectors5.2 Generating Intrinsic Reflection Images; 5.3 Restoring the Colors of Clipped and Bloomed Pixels; 5.4 The Use of Intrinsic Reflection Images; 5.5 Summary; 6: Results and Discussion; 6.1 Further Results; 6.2 Comparison with a Traditional Color Segmentation Algorithm; 6.3 Control Parameters; 6.4 Simplifying Heuristics; 6.5 Limitations of the Dichromatic Theory; 6.6 Summary; 7: Summary and Conclusions; 7.1 Contributions; 7.2 Directions of Future Research; 8: Related Work from 1988 until 1992; 8.1 Intrinsic Reflection Images |
|
8.2 Color Image Segmentation8.3 Reflection and Camera Models; 8.4 Analyzing Other Optical Phenomena; 8.5 Are We There Yet?; A: Derivation of the 50%-heuristic; B: Tables of illumination Geometries; C: Illumination Geometry for d = ∞; References; Index |
| Summary |
"The author presents a vision model that uses color information to interpret the effects of shading and highlights on a scene. Transcending more traditional approaches, this method may lead to more reliable and useful techniques for image understanding."--Provided by publisher |
| Bibliography |
Includes bibliographical references and index |
| Subject |
Computer graphics
|
|
Information visualization.
|
|
Image processing.
|
|
Computer Graphics
|
|
computer graphics.
|
|
image processing.
|
|
Computer graphics.
|
|
Image processing.
|
|
Information visualization.
|
| Form |
Electronic book
|
| Author |
Klinker, Gudrun, editor
|
| ISBN |
9781439864685 |
|
1439864683 |
|
