The Refine Method of Positioning Accuracy of Rational Function Model Based on Straight line features

Abstract:

This paper discussed the method which refines the RFM-based stereo positioning in object space based on known straight line features. For the two refine models (the Shift and main factor model and the Affine model), the formulas were derivated to solve the refine model parameters based on known straight line features. And the solution using known straight line features was given to compensate the RFM positioning error. The experimental results show that it is feasible to refine the RFM-based stereo positioning based on line features; and for the Shift and main factor model, the accuracy of using the straight line features is better than that using points, but for the Affine models, the accuracy of using straight line features is worse than that using points; furthermore, under the same condition, the accuracy of the former is also better than the latter.

Key words:Imaging model;Rational function model; Straight line features; Shift and main factor model; Affine model