Distortion Correction Method for Large Field-of-View Infrared Camera

This paper proposes a distortion correction method suitable for large field of view infrared cameras. First, the single-parameter division model is selected as the camera distortion model, and the improved speed-up robust features algorithm is used to automatically obtain the feature point pairs of two distorted infrared images with the same scene. The nine-point non-iterative algorithm and kernel density estimation method are then used to obtain the distortion parameters of the image. Finally, according to the obtained distortion parameters, the grayscale interpolation method based on edge preservation is used to correct the distortion of the image. In the entire process, it is not necessary to determine the parameters and scene information of the camera in advance, and the distortion correction is completed by entering two images with the same scene, which provides a new solution for the distortion correction of large-field infrared cameras. The experimental results show that it is feasible and robust to use this method to correct the distortion of large field infrared cameras.