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Introduction
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Tone Mapping Techniques and
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Acknowledgements
Contents
Introduction
Color Science Basics
Photometry and Radiometry
Light
Radiometry
Photometry
Colorimetry
Human Vision
Just Noticeable Difference
Brightness as a Function of Luminance
Brightness as a Function of Reflectance
Adaptation and Veiling Luminance
Contrast Sensitivity Function
Display Devices
Slides and Goldberg Rule
CRTs
Linear Scale-Factor Methods
Mean Value Mapping
Interactive Calibration
Logarithmic Histogram
Varying aperture
Varying contrast
Mapping of the Interval
Conclusion
Ward's Contrast Based Scale-factor
Non-Linear Scale-Factor Methods
Schlick's Mapping
Exponential Mapping
Tumblin and Rushmeier's Mapping
Model of Visual Adaptation
Visibility Matching Tone Reproduction Operator
Minimum Information Loss Methods
Minimum Information Loss Methods
Search for the Optimum Contrast Interval
How is it done in Photography?
Mean Light Method in Photography
Main Goal of the Optimization
Minimum Information Loss
Building a Logarithmic Histogram
Search for the Optimum Clipping Interval
Clipping Error
Minimum Area Loss
Mapping of the Interval
Limited Information Loss
Incident Light Metering
Light Metering in Photography
Incident Light Metering in Computer Graphics
Irradiance Computation
Simple Ray Tracing without Interreflections
Distribution Ray Tracing
Radiosity
Color Case
Conclusion and Future Work
Color Image Difference
Contrast Sensitivity Function
The Main Idea
Algorithm Details
Modified CIE LUV Color Difference Formula
Color Image Difference in a Distance Range
Image Query
Algorithm Summary
Conclusion and Future Work
Results
Tone Mapping Techniques
Color Image Difference
Conclusion
Raw Image File Formats
Radiance RGBE Format
Pixar's Log Format
SGI's LogLuv Format
References
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Next:
Introduction
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Tone Mapping Techniques and
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Acknowledgements
matkovic@cg.tuwien.ac.at
