Metric Information Extraction from Spot Images and the Role of Polynomial Mapping Functions

This paper handles the aspect of metric information extraction from SPOT images and focuses mainly on sensor modelling and the geometric accuracy potential of polynomial mapping functions, and secondly on the use of these functions for automated derivation of DTMs and generation of digital orthophotos. The sensor modelling is based on V. Kratky’s strict geometrical model. First, an accuracy analysis is provided based on points of varying definition quality covering the whole image format and having a height range of 1700 m. Different computation versions and an accuracy comparison is presented. Kratky also provides polynomial mapping functions to transform from image to image, object to image, and image to object space. The mapping functions are much faster, easier to implement, and almost equally accurate as compared to strict transformations. The accuracy of these functions will be assessed. This is crucial, since these polynomial functions are subsequently used for automatic DTM and orthophoto generation. The automatic DTM generation is based on a modified version of the Multiphoto Geometrically Constrained Matching (MPGC). The polynomial functions for the image to image transformation are used to define geometric constraints in image space. Thus, the search space is reduced along almost straight epipolar lines and the success rate and reliability of matching increase. The deviation of the epipolar lines from straight lines will be analysed for different image positions, heights and height approximations. The generation of digital orthophotos is fully automated and is based on polynomial functions modelling the object to image transformation. Aspects regarding speed and accuracy will be analysed.