RayChenPsych2012Project: Difference between revisions
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= References - Resources and related work = | = References - Resources and related work = | ||
A. Gijsenij, T. Gevers, J. van de Weijer. "Generalized Gamut Mapping using Image Derivative Structures for Color Constancy. | |||
J. van de Weijer, T. Gevers, A. Gijsenij. "Edge-Based Color Constancy" | |||
= Appendix I - Code and Data = | = Appendix I - Code and Data = | ||
==Code== | ==Code== |
Revision as of 21:01, 19 March 2012
Background
The human visual system features color constancy, meaning that the perceived color of objects remain relatively constant under varying lighting conditions. This helps us identify objects, as our brain lets us recognize an object as being a consistent color regardless of lighting environments. For example, a red shirt will look red under direct sunlight, but it will also look red indoors under fluorescent light.
However, if we were to measure the actual reflected light coming from the shirt under these two conditions, we would see that they differ. This is where problems arise. Think about the last time you took a picture with your digital camera, and the colors just seemed wrong. This is because cameras do not have the ability of color constancy. Fortunately, we can adjust for this by using color balancing algorithms.
Methods
Gray Edge
Results - What you found
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Conclusions
A. Gijsenij, T. Gevers, J. van de Weijer. "Generalized Gamut Mapping using Image Derivative Structures for Color Constancy.
J. van de Weijer, T. Gevers, A. Gijsenij. "Edge-Based Color Constancy"