Image Rectification Using a Generic Sensor Model – Rational Function Model

The Rational Function Model (RFM) has been considered as a generic sensor model. Compared to polynomial models widely used, RFM is essentially a more generic and expressive form. The RFM is technically applicable to all types of sensors such as frame, pushbroom, whiskbroom and SAR etc. With the increasing availability of the new generation imaging sensors, accurate and fast rectification of digital imagery using a generic sensor model becomes of great interest to the user community. In this paper, the technical viability of use of the RFM is examined. This paper firstly presents a brief overview of the geometric models used for the rectification of digital imagery. These models are the collinear equations based differential rectification model, the polynomial model, the projective transform model, the extended direct linear transform model and the RFM. The remarks on their properties, and the advantages and disadvantages for different models are discussed so that one will have a better understanding of the generic nature of the RFM. The two solution methods to the RFM, namely direct solution and iterative solution, are then provided. In fact, iterative solution is more rigorous in theory but requires many iterative steps to achieve the solution. Finally, the test results using real-world data sets are described. Comprehensive experiments have been carried out to evaluate the viability of the RFM solutions.