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Simulating Imaging of Large Scale Radio Arrays on the Lunar Surface
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Evaluation method for inter-chip uniformity in infrared mosaic arrays.

Lun Wang, Jinmei Zhou, Yu Wang

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    |April 15, 2026
    PubMed
    Summary

    This study introduces a novel method to evaluate infrared mosaic array uniformity using human perception. The approach combines neighborhood difference, Laplacian response, and local standard deviation metrics for accurate assessment.

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    Area of Science:

    • Optics and Photonics
    • Aerospace Engineering
    • Image Processing

    Background:

    • Infrared mosaic arrays enhance detection resolution in aerospace.
    • Evaluating inter-chip uniformity is crucial for optimal performance.
    • Existing methods may lack accuracy or robustness.

    Purpose of the Study:

    • To propose a robust and accurate method for evaluating inter-chip uniformity in infrared mosaic arrays.
    • To leverage human visual perception as a benchmark for uniformity assessment.
    • To develop a model that guides stitching and non-uniformity correction.

    Main Methods:

    • Selected three key metrics: neighborhood difference (ND), Laplacian response (LR), and local standard deviation (LSTD).
    • Fused these metrics using a support vector regression (SVR) model.
    • Employed leave-one-out cross-validation (LOOCV) for generalization assessment.

    Main Results:

    • The proposed method demonstrated satisfactory generalization on unseen configurations.
    • An ablation study confirmed the complementary nature and stable performance of the selected metrics.
    • Validation on independent datasets confirmed the method's robustness.

    Conclusions:

    • The developed evaluation method accurately characterizes inter-chip uniformity in infrared mosaic arrays.
    • This technique can guide the selection of stitching sequences and assess non-uniformity correction.
    • The approach offers a reliable tool for improving infrared imaging systems.