Calibration of TV cameras through RBF networks

Distortions are introduced by standard TVcameras on the filmed images. These are due to optics and electronics and cause a systematic displacement of the image points with respect to their true position which is given by the geometrical perspective. In order to correct this error, in classical photogrammetrical approaches, the coordinates of the points are transformed through global polynomials whose coefficients are estimated from a set of reference points placed on regular grids. These approaches do not work well when, as in most of the cases, the distortions are highly irregular, and residual errors over the images can be relatively high. In this paper a solution based on RBF networks is proposed. It takes advantage of the quasi-local nature of the network elements to get a uniform small residual distortion error over all the TV image. The structural parameters of the network (namely their number and variance) are set according to criteria inspired to linear filtering theory and the weights are computed following a MAP criterion. Tests on simulated distortions and on real data have been carried. The results reported here show that the RBF networks achieve a better reduction of the distortions in all the tested conditions.