Accurate estimation of camera response function for high dynamic range measurement

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.