Asymmetric lens distortion compensation method based on linear reconstruction of feature points

This paper proposes a new method to compensate for asymmetric lens distortion through feature point projection transformation and linear reconstruction. The method involves traversing the world coordinates of calibration image feature points using a minimum reference grid and calculating the composite projection transformation error of all grids. The composite projection error is obtained through weighted calculations based on linear constraints, cross-ratio constraints, and parallel line constraints. After a second screening, the reference grid area with the minimum projection error is identified. Subsequently, the optimal reference grid is optimized with the goal of minimizing the composite error. Finally, the optimized feature point coordinates are solved with the corresponding world coordinates to derive the homography matrix. This allows the linear reconstruction of the entire calibration image's feature points through projection transformation, and the parameters of the asymmetric lens distortion model are optimized. Consequently, a high-precision asymmetric lens distortion model is obtained, allowing for compensation and correction of the asymmetric distortion.