一种大视场红外相机的畸变校正方法

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

  • 摘要: 本文针对大视场红外相机的畸变校正过程复杂的问题,提出了一种新的畸变校正方法。首先,选择单参数除法模型(division model,DM)作为相机畸变模型,使用改进的加速特征稳健算法(speed-up robust features,SURF)自动获取两幅有相同场景的畸变红外图像的特征点对,然后利用九点非迭代算法和核密度估计方法获取图像的畸变参数,最后根据求得的畸变参数使用基于边缘保持的灰度插值方法对图像进行畸变校正。在整个过程中,不需要预先知道相机的参数和场景信息,通过输入两幅具有相同场景的图像,完成畸变校正,为大视场红外相机的畸变校正提供了一种新的解决方法。实验结果表明,使用该方法对大视场红外相机进行畸变校正具有可行性和鲁棒性。

     

    Abstract: 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.

     

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