Hi,

On 03/21/2017 09:18 AM, Agustin Lobo wrote:
I guess the second. Examples:
http://geog.uoregon.edu/amarcus/geog418/Labs/Lab06_rectification.htm

The polynomial can be fit and applied using gdal_translate to
incorporate the GCPs and then
gdalwarp r near order 2
to apply the transformation

but the way of introducing the GCPs is kind of inconvenient.
This problem is more about sensor model fitting. You have an image in sensor geometry and you try to ortho-rectify it on ground based on a set of GCPs. The OTB already has an application to assess a RPC sensor model based on GCPs.

The polynomial model is a particular case of rational model, maybe setting the denominator coefficients to [1,0,0,...,0] will do the trick.

Guillaume

Yes, I agree. But can this be done in practice? Also, is there a tool
in OTB to actually fit such a rational polynomial with prescribed
denominators?
No, at the moment there is no way to estimate a polynomial transform based on GCPs. If the transform is already computed, it can be fed into a *.geom file to act as a RPC model with denominator coefficients set like proposed.

Anyway, please consider also my suggestion of including the method described in
Pala, V., and X. Pons. 1995. “Incorporation of Relief in
Polynomial-Based Geometric Correction.” Photogrametrics Engineering &
Remote Sensing 61: 935–44.
https://www.researchgate.net/publication/244485309_Incorporation_of_relief_polynomial-based_geometric_corrections
The sensor models in OTB (RPC based or physical) should already take into account elevation. The inverse localization function is modeled like :
    (row,col) = F_inv(x,y,z)


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