A New Approach on Optimization of the Rational Function Model of High-Resolution Satellite Imagery

Overparameterization is one of the major problems that the rational function model (RFM) faces. A new approach of RFM parameter optimization is proposed in this paper. The proposed RFM parameter optimization method can resolve the ill-posed problem by removing all of the unnecessary parameters based on scatter matrix and elimination transformation strategies. The performances of conventional ridge estimation and the proposed method are evaluated with control and check grids generated from Satellites d'observation de la Terre (SPOT-5) high-resolution satellite data. Experimental results show that the precision of the proposed method, with about 35 essential parameters, is 10% to 20% higher than that of the conventional model with all 78 parameters. Moreover, the ill-posed problem is effectively alleviated by the proposed method, and thus, the stability of the estimated parameters is significantly improved.