High-Precision Camera Distortion Correction: A Decoupled Approach With Rational Functions.

Area of Science:

• Computer Vision
• Geometric Imaging

Background:

• Camera distortion is a significant challenge in precision-critical fields like medical imaging, robotics, and 3D reconstruction.
• Traditional radial-symmetry models have limited precision and require complex optimization, creating a gap for more robust solutions.

Purpose of the Study:

• To present a robust, decoupled camera distortion correction method using the Rational Function Model (RFM).
• To address the practical applicability gap of RFM concerning robustness, noise, and sample distribution.

Main Methods:

• Mathematical interpretation of RFM suitability via sensitivity analysis.
• Evaluation of RFM precision and robustness using synthetic and real-world experiments.
• Development of a decoupled distortion correction method using a single chessboard image.

Main Results:

• RFM demonstrates suitability for distortion correction, with precision and robustness validated across various conditions.
• The proposed decoupled method achieves practical and accurate distortion correction.
• Enhanced distortion correction improves overall camera calibration accuracy.

Conclusions:

• The decoupled RFM-based approach offers a flexible, high-precision solution for distortion correction.
• This method simplifies calibration steps and ensures reliable geometric accuracy.
• Establishes a foundation for distortion-free imaging and simplified camera models in computer vision.