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Correcting distortion of image by image registration with the implicit function theorem

机译:使用隐函数定理通过图像配准校正图像失真

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摘要

We propose a method for correcting image distortion due to camera lenses by calibrating intrinsic camera parameters. The proposed method is based on image registration and doesn't require point-to-point correspondence. Parameters of three successive transformations view change, radial distortion and illumination change are estimated using the Gauss-Newton method. Estimating all 19 unknowns simultaneously, we introduce the implicit function theorem for calculating the Jacobian. To avoid local minima, we first estimate parameters for view change and employ coarse-to-fine minimization. Experimental results using real images demonstrate the robustness and the usefulness of the proposed method.
机译:我们提出了一种通过校准相机固有参数来校正由于相机镜头引起的图像失真的方法。该方法基于图像配准,不需要点对点的对应关系。使用高斯-牛顿法估计三个连续变换的参数,即视图变化,径向变形和照明变化。同时估计所有19个未知数,我们引入隐式函数定理来计算雅可比行列式。为了避免局部最小值,我们首先估计用于视图更改的参数,然后采用从粗到精的最小化方法。使用真实图像的实验结果证明了该方法的鲁棒性和实用性。

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