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Rational function model for sensor orientation of IRS-P6 LISS-4 imagery

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This paper explores the application of a rational function model (RFM) as a replacement sensor model for IRS-P6 LISS-4 imagery. The rational polynomial coefficients (RPCs), initially generated using a rigorous sensor model (RSM) through direct georeferencing, are bias-compensated with a minimum number of ground control points and are used for various photogrammetric applications such as digital elevation model and ortho-image generation. The performance of RFM and RSM is compared in the sensor modelling of LISS-4 imagery over long strips. Results show that accuracies achieved using RFM are within 1 pixel (worst case) of the accuracies derived using RSM. Error variation as a function of the number of quasi-control points (anchor points) used for RFM fitting as well as model errors with respect to the length of the image strip are analysed. System-level accuracy does not deteriorate when the RFM is fitted up to a length of 1200 km. Absolute positioning accuracy of 1ยท5 pixels (∼9 m) is achieved from bias-compensated RPCs. The results demonstrate the potential of RFM as a replacement sensor model. This allows standardisation of product generation packages to handle multiple sensors.

Keywords: IRS-P6; LISS-4; anchor points; rational function model; rational polynomial coefficients; rigorous sensor model

Document Type: Research Article


Affiliations: 1: ( ), Email: 2: ( ), Email: 3: ( ), Email: 4: ( ) Advanced Data Processing Research Institute, Department of Space, Hyderabad, India, Email:

Publication date: December 1, 2007

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