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Updated: Jan 19, 2026

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
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Atmospheric cloud algorithms for day/night whole sky imagers.

Janet E Shields, Art R Burden, Monette E Karr

    Applied Optics
    |September 11, 2019
    PubMed
    Summary
    This summary is machine-generated.

    New atmospheric cloud algorithms accurately detect and categorize clouds using day/night whole sky imagers. These algorithms provide precise, pixel-by-pixel cloud detection under various lighting conditions, including starlight.

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    Area of Science:

    • Atmospheric science
    • Remote sensing
    • Cloud physics

    Background:

    • Accurate cloud detection is crucial for meteorological and climate studies.
    • Existing cloud algorithms face challenges in varying light conditions (day, night, starlight).
    • Whole sky imagers offer comprehensive sky coverage but require robust algorithms for data interpretation.

    Purpose of the Study:

    • To introduce novel day and night cloud detection and classification algorithms.
    • To assess the accuracy of these newly developed algorithms.
    • To evaluate the performance of visible and near-infrared spectral bands for cloud analysis.

    Main Methods:

    • Development of day cloud algorithm using red/blue ratios and clear sky comparisons.
    • Implementation of adaptive features for haze adjustment in day and night algorithms.
    • Design of night cloud algorithms based on earth-to-space beam transmittances and radiance comparisons.

    Main Results:

    • Algorithms provide pixel-by-pixel cloud detection and opacity categorization with excellent accuracy.
    • Day algorithm distinguishes opaque and thin clouds effectively.
    • Night algorithms accurately determine cloud presence and report earth-to-space beam transmittance.

    Conclusions:

    • The developed algorithms offer a significant advancement in cloud detection capabilities.
    • The algorithms are effective across diverse lighting conditions, including low-light starlight.
    • The study validates the utility of specific spectral bands for atmospheric cloud analysis.