  Nonlinear lens distortion rectification is a common first step in image
processing applications where the assumption of a linear camera model is
essential. For rectifying the lens distortion, forward distortion model needs
to be known. However, many self-calibration methods estimate the inverse
distortion model. In the literature, the inverse of the estimated model is
approximated for image rectification, which introduces additional error to the
system. We propose a novel distortion rectification method that uses the
inverse distortion model directly. The method starts by mapping the distorted
pixels to the rectified image using the inverse distortion model. The resulting
set of points with subpixel locations are triangulated. The pixel values of the
rectified image are linearly interpolated based on this triangulation. The
method is applicable to all camera calibration methods that estimate the
inverse distortion model and performs well across a large range of parameters.
