2005/01/01 by Keigo Hirakawa, T.W. Parks · 1 citation
Computer Science · Mathematics · Neuroscience · Physics and Astronomy · Psychology · #Adaptation (eye) #Algorithm #Artificial intelligence #Balance (ability) #Chromatic adaptation #Color Science and Applications #Color balance #Color constancy #Color image #Computer science #Computer vision #Image (mathematics) #Image Enhancement Techniques #Image processing #Mathematical optimization #Mathematics #Psychology #Standard illuminant #Visual perception and processing mechanisms #White (mutation)
paper · doi:10.1109/icip.2005.1530559
openalex publication_date 2005/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
The problem of adjusting the color such that the output image from a digital camera, viewed under a standard condition, matches the scene observed by the photographer's eye is called white-balance. While most white-balance algorithms approach the problem using the coefficient law (von Kries), the coefficient law has been shown inaccurate. In this paper, we instead formulate the white-balance problem using Jameson and Hurvich's induced opponent response chromatic adaptation theory. The solution to this white-balance problem reduces to a single matrix multiplication. The experimental results using existing illuminant estimation methods verify that the induced opponent response approach to solving the white-balance problem yields more neutral colors in the white panels of the Macbeth color chart than the traditional methods. The computational cost of the proposed method is virtually zero.