Spectral Illumination Correction: Achieving Relative Color Constancy Under the Spectral Domain

Achieving color constancy between and within images, i.e., minimizing the color difference between the same object imaged under nonuniform and varied illuminations is crucial for computer vision tasks such as colorimetric analysis and object recognition. Most current methods attempt to solve this by...

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Bibliographic Details
Published in2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) pp. 690 - 695
Main Authors Yunfeng Zhao, Elliott, Chris, Huiyu Zhou, Rafferty, Karen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2018
Subjects
algorithm
Calibration
camera calibration
Cameras
color constancy
illumination correction
Image color analysis
Lighting
Mathematical model
pixel-wise
Spectral analysis
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DOI10.1109/ISSPIT.2018.8642637

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Summary:Achieving color constancy between and within images, i.e., minimizing the color difference between the same object imaged under nonuniform and varied illuminations is crucial for computer vision tasks such as colorimetric analysis and object recognition. Most current methods attempt to solve this by illumination correction on perceptual color spaces. In this paper, we proposed two pixel-wise algorithms to achieve relative color constancy by working under the spectral domain. That is, the proposed algorithms map each pixel to the reflectance ratio of objects appeared in the scene and perform illumination correction in this spectral domain. Also, we proposed a camera calibration technique that calculates the characteristics of a camera without the need of a standard reference. We show that both of the proposed algorithms achieved the best performance on nonuniform illumination correction and relative illumination matching respectively compared to the benchmarked algorithms.
DOI:10.1109/ISSPIT.2018.8642637