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Title: An iterative optimization algorithm for lens distortion correction using two-parameter models
Authors: Santana Cedres, Daniel Elias 
Gómez Déniz, Luis 
Alemán Flores, Miguel 
Salgado de la Nuez, Agustín 
Esclarín Monreal, Julio 
Mazorra, L. 
Alvarez, L 
UNESCO Clasification: 120602 Ecuaciones diferenciales
120326 Simulación
120601 Construcción de algoritmos
220990 Tratamiento digital. Imágenes
Keywords: Calibration
Issue Date: 2016
Journal: Image Processing On Line 
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.Source CodeThe source code, the code documentation, and the online demo are accessible at the IPOL web page of this articlel In this page, an implementation is available for download. Compilation and usage instructions are included in the README.txt file of the archive.
ISSN: 2105-1232
DOI: 10.5201/ipol.2016.130
Source: Image Processing On Line[ISSN 2105-1232],v. 6, p. 326-364, (2016)
Appears in Collections:Artículos
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