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1 | initial version |

I have also run into this issue with my setup, although my lens distortion isn't even that heavy. I also had the problem with the calculation of the inner and outer rectangles for determining the new camera matrices. The way OpenCV calculates these inner and outer rectangles is based on the assumption that the radial distortion is monotonic, so they assume that the edges of the input images should contain the most heavily distorted points and only sample along the image border for determining the most extreme distortion.

This however, is not necessarily the case, when you use the higher order radial model (with k_2 and k_3) or the "rational" model it is possible that the camera calibration converges to a set of distortion parameters that are not monotonic, and so these assumptions are invalid and resulting inner and outer rectangles make no sense, as can be seen in the example image by Thomas. This has happened to me on occasion, where the outer third of my image has a lower distortion factor than the inner two thirds an increasing warp factor.

I think the only real solution to this would be to modify the camera calibration optimization objective function to include constraints so that the distortion factors are monotonic throughout the image.

2 | No.2 Revision |

I have also run into this issue with my setup, although my lens distortion isn't even that heavy. I also had the problem with the calculation of the inner and outer rectangles for determining the new camera matrices. The way OpenCV calculates these inner and outer rectangles is based on the assumption that the radial distortion is monotonic, so they assume that the edges of the input images should contain the most heavily distorted points and only sample along the image border for determining the most extreme distortion.

This however, is not necessarily the case, when you use the higher order radial model (with k_2 and k_3) or the "rational" model it is possible that the camera calibration converges to a set of distortion parameters that are not monotonic, and so these assumptions are invalid and resulting inner and outer rectangles make no sense, as can be seen in the example image by Thomas. This has happened to me on occasion, where the outer third of my image has a lower distortion factor than the inner two ~~thirds an increasing warp factor.~~thirds.

I think the only real solution to this would be to modify the camera calibration optimization objective function to include constraints so that the distortion factors are monotonic throughout the image.

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