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Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
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Updated: May 30, 2025

Visualizing Visual Adaptation
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Universal scale laws for colors and patterns in imagery.

Rémi Michel, Mohamed Tamaazousti

    Journal of the Optical Society of America. A, Optics, Image Science, and Vision
    |January 31, 2025
    PubMed
    Summary

    Fully Colored Images (FCIs) exhibit universal properties in color and pattern distribution, adhering to specific mathematical laws regardless of scale. These findings have implications for neural networks and physics.

    Area of Science:

    • Image analysis
    • Complex systems
    • Statistical physics

    Background:

    • The distribution of colors and patterns in natural images is complex.
    • Previous research has explored scaling laws in image properties, but universal adherence remains debated.

    Purpose of the Study:

    • To investigate universal properties in the distribution of colors and patterns within Fully Colored Images (FCIs).
    • To determine if these properties adhere to established mathematical laws across different scales and dynamics.

    Main Methods:

    • Analysis of color and pattern cascades in images by adjusting spatial resolution and dynamics.
    • Derivation of discrete 2x2 patterns from pixel reductions onto rotation-free textures.
    • Application of the continuous linear log-scale law (L1), entropy analysis (L2), and the Integral Fluctuation Theorem (L3).

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    Main Results:

    • FCIs of natural scenes universally adhere to a continuous linear log-scale law (slope -2.00±0.01).
    • Discrete patterns exhibit a universal entropy maximum (1.74±0.013) and adhere to the Integral Fluctuation Theorem (1.00±0.01).
    • Images with fewer colors deviate from L1 and L3 but still adhere to L2; fractal FCIs better match these laws than simulations.

    Conclusions:

    • Natural image properties exhibit universal adherence to specific mathematical laws, particularly concerning color and pattern distribution.
    • These findings offer insights into complex systems, potentially impacting fields like Neural Networks and out-of-equilibrium physics.
    • The study highlights the significance of fractal properties in matching observed image laws.