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Accurate estimation of camera response function for high dynamic range measurement.

Ji Li, Jingtian Guan, Yukun Wang

    Applied Optics
    |February 24, 2022
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    Summary
    This summary is machine-generated.

    Accurate identification of saturated pixels is crucial for high dynamic range surface measurement. This study introduces a camera response function (CRF) estimation method to precisely detect saturated pixels, improving measurement accuracy.

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    Area of Science:

    • Optics and Photonics
    • Computer Vision
    • Metrology

    Background:

    • High dynamic range (HDR) surfaces exhibit significant reflectivity variations.
    • Structured light techniques for measuring HDR surfaces can lead to pixel saturation, compromising accuracy.
    • Accurate identification of saturated pixels is essential for reliable HDR measurements.

    Purpose of the Study:

    • To develop an accurate camera response function (CRF) estimation approach for HDR measurement.
    • To propose a novel method for identifying saturated pixels using the estimated CRF.
    • To enhance the accuracy of structured light measurements on HDR surfaces.

    Main Methods:

    • Developed an accurate camera response function (CRF) estimation algorithm.
    • Implemented a saturation identification method utilizing the estimated CRF.
    • Conducted comparative experiments against existing saturation identification techniques.

    Main Results:

    • The proposed method demonstrated superior saturation identification accuracy compared to existing methods.
    • Experimental results validated the effectiveness of the CRF-based saturation identification.
    • Improved measurement accuracy on high dynamic range surfaces was achieved.

    Conclusions:

    • The proposed CRF estimation and saturation identification method significantly enhances measurement accuracy for HDR surfaces.
    • This approach offers a robust solution for overcoming pixel saturation challenges in structured light measurements.
    • The method is accurate and suitable for practical applications in metrology and computer vision.