| Summary: | 碩士 === 國立臺灣大學 === 電子工程學研究所 === 96 === Abstract
Humans are able to recognize the color of objects independently of the light
sources, which is called as color constancy. In a digital still camera, a sensor
is used to measure the reflected light, and the measured color at each pixel varies
according to the color of the illuminant. Therefore, the resulting colors may not
be the same as those perceived by users. Many algorithms have been developed to
solve the color constancy problem, which is sometimes also called as auto white
balance. Since digital cameras and mobile phones equipped with cameras became
more and more popular in recently years, the selection of color constancy
algorithms for realtime system implementation is an important issue.
In this thesis, we first provide a comprehensive introduction to the field of
color constancy, where the major color constancy algorithms are described. The
performance of these algorithms are then evaluated, and the hardware cost of some
algorithms are analyzed with a proposed system framework. Furthermore, based
on the analysis results, we also propose a new algorithm by taking advantages
of existing Gamut Mapping and modified Gary World algorithms. Gamut Mapping
algorithm is employed when the number of recognized illuminants is small
enough, and modified Gray World algorithm is employed for other cases. After
comparing with other color constancy methods with a large date sets of images
recording objects under different light sources, the experiments show that the proposed
color constancy algorithm achieves the best performance with acceptable
hardware cost.
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