International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004
with different radiometric and scale properties. For example,
aerial or satellite images may differ from each other with respect
to scale, spectral range of recording, image quality and imaging
conditions (weather, lighting). In practice, matching
heterogeneous images may prove to be more difficult than
implementing the triangulation of different sensor models.
Rigorous analysis on the error propagation for cross sensor
photogrammétric processing is also of great importance since
the imaging geometry and the accuracies may be different
among multiple satellites and sensors. However, the difference
of fitting accuracy of the RPC models to individual physical
sensor models seems neglectable since the accuracy loss is
neglectable for the terrain-independent approach.
8. CONCLUDING REMARKS
Some high-resolution satellite imagery vendors such as Space
[Imaging and Digital Globe currently provide the RPCs to end
users and service providers to allow for photogrammetric
processing. This technology simplifies the complicated
photogrammetric mapping process to a great extent, and has
been proved to be a useful tool for exploiting high-resolution
satellite images. The RFM may be used to replace the rigorous
sensor models for many mapping applications because high
accuracies have been achieved in exploiting images. And the
scepticism on the accuracy achievable has been replaced with a
wide the adoption of this technology.
This paper provides an overview of various aspects in
developing the RFM, including computational scenarios,
accuracy assessment, RFM refinement, photogrammetric
interoperability, and mapping applications. Photogrammetrists
have overcome restrictions placed on the use of the data by
vendors using RFM refining methods, which ensure that the
exploitation results are as accurate as what can be achieved
using physical sensor models, and are also economical using
low price products. The RFM provides an open standard for
photogrammetric interoperability, is not dependent on particular
sensors, and is extensible for block adjustment. In summary,
although there are still remaining issues, the RFM is likely to
become a passkey in geometry modeling of various sensors.
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