基于精确模型和逆投影的超大视场红外图像畸变校正

Ultra-wide FOV Infrared Image Distortion Correction Based on Accurate Model and Back-projection

摘要:

针对超大视场红外图像畸变大、与人眼视觉差异明显的问题,提出了一种基于精确模型和逆投影的超大视场红外图像畸变校正算法以改善其视觉效果。该算法首先利用精确模型对超大视场红外相机成像中的物、像关系进行描述；然后,针对红外图像像素采样率不高的缺点,利用较为精确的三次卷积插值法对图像进行插值来补全成像信息；最后,根据校正图像上的待赋值像点的坐标,结合校正模型和超大视场红外相机精确模型,计算该像点逆投影到插值图像时的对应坐标,并以最近邻像点像素值作为校正后图像像点的赋值。车载道路场景下的超大视场红外图像畸变校正实验结果显示,所提出的算法图像校正结果边界清晰、无锯齿效应,对场景中的直线平均还原偏差小于0.35pixels,表明该算法对超大视场红外图像畸变校正具有较好的适用性。

Abstract:

In order to solve the problems of large distortion of ultra-wide field of view (FOV) infrared image and obvious difference from human vision, in this paper, an ultra-wide FOV infrared image distortion correction algorithm is proposed based on accurate model and back-projection. The algorithm first describes the relationship between object point and image point in the ultra-wide FOV infrared camera imaging by using the accurate model. Then, aiming at the disadvantage of low sampling rate of infrared image pixels, the more accurate cubic convolution interpolation method is used to interpolate the image for completing the imaging information. Finally, according to the point coordinates of corrected image, combined with the correction model and the accurate model, the corresponding coordinates on the ultra-wide FOV infrared image point coordinates are calculated by backward projection. The pixel value of the nearest image point is used as the value of the corrected image point. The experimental results show that the proposed algorithm has clear boundary and no sawtooth effect, and the average restoration error of the straight line in the scene is less than 0.35 pixels, which indicates that the algorithm has excellent applicability for the distortion correction of the ultra-wide FOV infrared image.