Image distortion correction technology in imaging systems

In consideration of the effect of the image distortion on the measurement accuracy in imaging system, a method of image distortion correction based on Zernike vector polynomials is proposed. The coordinates of the fiducial points both in reference map and distorted map are normalized in a unit circle, and the mapping relation between reference map and distorted map is fitted with the Zernike vector polynomials. The correction of the distorted image is implemented by using the mapping relation which is discovered by use of the Zernike vector polynomials fitting method. In order to reduce the data discontinuity, the corrected map is also interpolated. Then the correction results are evaluated and compared with the camera calibration toolbox for Matlab method. The experimental results indicate that compared with the latter, using the Zernike vector polynomials method can reduce the root mean square (RMS) error due to the radial distortion by nearly 50%, and can reduce the RMS error due to the keystone distortion to 10^-3 magnitude order.