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    This study introduces a new physics-based method for estimating illumination in natural images, even with ambient light. It accurately determines illuminant chromaticity by finding the longest dichromatic line from specular pixels, improving upon existing color constancy techniques.

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    Area of Science:

    • Computer Vision
    • Image Processing
    • Computational Photography

    Background:

    • Existing physics-based color constancy methods often fail with natural images due to the assumption of a single illuminant.
    • Ambient light introduces errors in specular pixel analysis, leading to inaccurate dichromatic lines and significant estimation errors.

    Purpose of the Study:

    • To develop a physics-based illumination estimation approach robust to ambient light conditions in natural images.
    • To improve the accuracy of illuminant chromaticity estimation by addressing limitations of current color constancy methods.

    Main Methods:

    • Utilizing the Phong reflection model to analyze specular pixels on uniformly colored objects.
    • Identifying the optimal image path that yields the longest dichromatic line from specular pixels.
    • Developing a method to find ambient-robust specular pixels based on dichromatic line length.

    Main Results:

    • The proposed method accurately estimates illuminant chromaticity even with reduced specular pixel sets.
    • Specular pixels identified via the longest dichromatic line provide more accurate chromaticity estimations.
    • Experimental results demonstrate superior performance compared to state-of-the-art color constancy methods.

    Conclusions:

    • The novel approach effectively handles ambient light in illumination estimation for natural images.
    • This method offers a more reliable way to determine illuminant chromaticity, advancing color constancy research.
    • The technique shows significant potential for applications requiring accurate color interpretation in complex lighting.