光场相机建模与畸变校正改进方法

Light field camera modeling and distortion correction improvement method

  • 摘要: 光场相机作为一种新型的成像系统,可以直接从一次曝光的图像中得到三维信息。为了能够更充分有效地利用光场数据包含的角度和位置信息,完成更加精准的场景深度计算,从而提升光场相机的三维重建的精度,需要实现精确的几何建模,并精确标定其模型参数。该方法从薄透镜模型和小孔成像模型出发,将主透镜建模为薄透镜模型,将微透镜建模为小孔成像模型,结合光场相机双平面模型,将每个提取到的特征点与其在三维空间中的射线建立联系,详细解释了内参矩阵中每个参数的物理意义,以及标定过程中初值确定的过程,并在镜头径向畸变模型的基础上进一步应用了相机镜头的切向畸变模型以及基于射线重投影误差的非线性优化方法,改进了光场相机的标定方法。实验显示,该方法的RMS射线重投影误差为0.332 mm,与经典的Dansereau标定方法相比,进行非线性优化后得到的射线重投影误差精度提升了8%。该方法详细分析的场景点与特定像素索引的推导过程对光场相机的标定具有重要的研究意义,为光场相机光学模型的建立与初始化标定奠定了基础。

     

    Abstract: As a new type of imaging system, the light field camera can directly obtain 3D information from a single exposure of the image. In order to make more sufficient and effective use of the angle and position information contained in the light field data, complete more accurate scene depth calculation, and thus improve the accuracy of the 3D reconstruction of the light field camera, it is necessary to establish accurate geometric modeling and precisely calibrate its model parameters. This method starts from the thin lens model and pinhole imaging model, the main lens is modeled as the thin lens model, the micro modeling for pinhole imaging model, combined with the two-parallel-plane model of the light field camera, each extracted feature point is associated with its ray in three-dimensional space, the physical meaning of each parameter in the internal reference matrix is explained in detail, as well as the process of determining the initial value in the process of calibration. Furthermore, based on the radial lens distortion model, the tangential lens distortion model and the nonlinear optimization method based on ray reprojection error are further applied to improve the calibration method of light field camera. The experimental results show that the RMS ray reprojection error of this method is 0.332 mm. Compared with the classical Dansereau calibration method, the ray reprojection error accuracy of the proposed method is improved by 8% after nonlinear optimization. The derivation process of scene points and specific pixels analyzed in detail in this method has important research significance for the calibration of optical field cameras, which lays the foundation for establishment of optical model and the initial calibration of light field cameras.

     

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