An Iterative Optimization Algorithm for Lens Distortion Correction Using Two-Parameter Models
Daniel Santana-Cedrés, Luis Gómez, Miguel Alemán-Flores, Agustín Salgado, Julio Esclarín, Luis Mazorra, Luis Álvarez
→ BibTeX
@article{ipol.2016.130,
    title   = {{An Iterative Optimization Algorithm for Lens Distortion Correction Using Two-Parameter Models}},
    author  = {Santana-Cedrés, Daniel and Gómez, Luis and Alemán-Flores, Miguel and Salgado, Agustín and Esclarín, Julio and Mazorra, Luis and Álvarez, Luis},
    journal = {{Image Processing On Line}},
    volume  = {6},
    pages   = {326--364},
    year    = {2016},
    doi     = {10.5201/ipol.2016.130},
}
% if your bibliography style doesn't support doi fields:
    note    = {\url{https://doi.org/10.5201/ipol.2016.130}}
published
2016-12-18
reference
Daniel Santana-Cedrés, Luis Gómez, Miguel Alemán-Flores, Agustín Salgado, Julio Esclarín, Luis Mazorra, and Luis Álvarez, An Iterative Optimization Algorithm for Lens Distortion Correction Using Two-Parameter Models, Image Processing On Line, 6 (2016), pp. 326–364. https://doi.org/10.5201/ipol.2016.130

Communicated by Pascal Monasse
Demo edited by Agustín Salgado

This IPOL article is related to a companion publication in the SIAM Journal on Imaging Sciences:
D. Santana-Cedrés, L. Gómez, M. Alemán-Flores, A. Salgado, J. Esclarin, L. Mazorra, and L. Alvarez.
"Invertibility and Estimation of Two-Parameter Polynomial and Division Lens Distortion Models" SIAM Journal on Imaging Sciences 8(3):1574-1606, 2015. http://dx.doi.org/10.1137/151006044


Abstract

We present a method for the automatic estimation of two-parameter radial distortion models, considering polynomial as well as division models. The method first detects the longest distorted lines within the image by applying the Hough transform enriched with a radial distortion parameter. From these lines, the first distortion parameter is estimated, then we initialize the second distortion parameter to zero and the two-parameter model is embedded into an iterative nonlinear optimization process to improve the estimation. This optimization aims at reducing the distance from the edge points to the lines, adjusting two distortion parameters as well as the coordinates of the center of distortion. Furthermore, this allows detecting more points belonging to the distorted lines, so that the Hough transform is iteratively repeated to extract a better set of lines until no improvement is achieved. We present some experiments on real images with significant distortion to show the ability of the proposed approach to automatically correct this type of distortion as well as a comparison between the polynomial and division models.

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