Accurate image correction of navigation cameras and hazard avoidance cameras for ten-parameter calibration model
The ten-parameter calibration model is a classical internal parameter calibration model in near-field photogrammetry.Using this model in image distortion correction,if direct resampling is used,it will produce hollow streaks,while the conventional indirect resampling method does not produce hollows,but it also fails to get better correction effect in the non-central region with large distortion.In order to address this problem,this paper proposes an image Newton iterative accurate correction algorithm for the ten-parameter calibration model.Firstly,the ten-parameter calibration model is used to reorganize the ideal value and actual value of the image point,and construct a system of nonlinear equations with the actual value of the image point as the quantity to be solved;then Newton iteration is used to solve the local linear approximation of the aberrant part of the image;and finally,indirect resampling is used to realize the purpose of accurate correction.Taking the navigation and obstacle avoidance camera of mobile robot as the research object,the experimental results show that the Newton's iterative method of correction can obtain high-precision and high-quality de-distorted images,and the processing effect on the obstacle avoidance camera is especially significant.The algorithm proposed in this paper is suitable for the accurate removal of aberrations from robot's navigation cameras and hazard avoidance cameras,and provides a reliable data source for the generation of high-quality binocular kernel line images for the subsequent stereo matching process.
万方数据
维普
