Camera Distortion Calibration through Fringe Pattern Phase Analysis

Abstract: The goal of this thesis is to use fringe-pattern phase analysis to calibrate the distortion of a camera lens. The benefit of using this method is that the distortion can be calculated using data from each individual pixel and the methodology does not need any model. The phase used to calibrate the images is calculated in two different ways, either utilizing the monogenic signal or through fringe-pattern phase analysis. The calibration approaches were also validated through different methods. Primarily by utilizing the Hough transform and calibrating simulated distortion. The thesis also introduces a validation approach utilizing the phase orientation calculated through the monogenic signal. The thesis also implements different approaches such as flat field correction to limit the impact of the image sensor noise to mitigate the phase noise. It is also investigated which fringe-pattern frequencies are best suited for calibration through comparative analysis. The comparative analysis identified problems with too high and low frequencies of the fringe-patterns when calibrating using fringe-pattern phase analysis.