Comparison between Algorithms of Ortho-rectification forRemote Sensing Images

There are kinds of methods for ortho-rectification in application of remote sensing images,including Collinearity Equation Model,Strict Geometric Model based on Affine Transformation,Improved Polynomial Model,Rational Function Model,Method based on Neural Network,and so on.But there is lack of system comparison among these methods.On the basis of introducing the principle of the methods above,advatanges and drawbacks about these algorithms are summarized in this paper.Specific emphasis is the mathematical derivation and algorithm design of FM.Tikhonov method is taken to the progress of computation of RFM.Two kinds of algorithm based on neural network was taken in application of ortho-rectification.To compare accuracy and effectiveness between the above methods,we make some experiments.The result shows that: on the condition of the same GCPs distribution,Rational Function Model that can reach sub pixel accuracy is the best of all from the viewpoint of precision and can be used in practice in spite of its relatively slower speed.