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Color correction for multi-camera systems: aligning white points.

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    Color differences in multi-camera systems are often due to inconsistent white points, not spectral sensitivity. A new calibration method using selected light sources and a conversion matrix improves real-time color consistency for better user experience.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Color Science

    Background:

    • Modern devices like smartphones and drones utilize multiple cameras with varying focal lengths and fields of view (FOVs).
    • Sequential image capture with different FOVs often results in noticeable color discrepancies, negatively impacting user experience.
    • Previous research primarily attributed these color shifts to differing spectral sensitivity functions of cameras.

    Purpose of the Study:

    • To investigate the primary cause of color differences observed in images captured by multiple cameras with different FOVs.
    • To develop and validate a method for enhancing color consistency across images from different cameras.

    Main Methods:

    • Identified inconsistent white point estimation as the main driver of color differences.
    • Proposed a novel camera calibration method using carefully selected calibration light sources.
    • Implemented a conversion matrix for real-time white point alignment among images.

    Main Results:

    • The proposed method effectively addresses color inconsistencies arising from differing white points.
    • Real-time white point alignment significantly improved the perceived color consistency between images.
    • The findings challenge the prevailing attribution of color differences solely to spectral sensitivity.

    Conclusions:

    • Inconsistent white point estimation is the predominant factor causing color differences in multi-camera systems.
    • The developed calibration and alignment technique offers a practical solution for achieving superior color consistency.
    • This research provides a pathway to enhance the visual quality and user experience in multi-camera imaging applications.