Auto White Balance Algorithm in Few Colors and No-White-Point Scenes
Date Issued
2011
Date
2011
Author(s)
Tsai, Chung-Yung
Abstract
Due to convenience and popularity of digital cameras, making cameras much easier to use is important in developing new photography technology. Different from the human visual system, which has the ability to automatically adjust color perceived, digital light sensor such as Charge Coupled Device (CCD) and Complementary Metal Oxide Semiconductor (CMOS) can only record intensity of incident photons, namely, producing the color cast in the original image. The goal of white balance is using post-processing techniques to remove the color cast-producing images similar to those perceived by human.
In traditional methods, color deficient and no-white-point scenes are situations that are hard to yield good results. To solve this problem, this thesis proposes a new method: Multiple Curve Color Temperature Estimation, which (i) constructs reference curves corresponding to different colors, (ii) calculates color temperature distance (CTD) between the averaged R-Gain/B-Gain values of each segmented area and reference curves, (iii) calculates probable color temperature of segmented area and confidence level about this color temperature using the CTDs, and (iv) estimates color temperature of the whole image using probable color temperatures and confidences. Different algorithms are used, and the result and performance of each method are analyzed. The result showed that the proposed method outperformed the traditional methods when dealing with no-white-point and color deficient scenes.
Subjects
auto white balance
color temperature
digital image processing
color constancy
Type
thesis
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