The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
5. CONCLUSIONS
In this paper we have shown two new methods for the
correction of atmospheric and BRDF effects in ADS40 images
which will be implemented in the new ADS40 radiometric
imaging chain. In contrast to the existing atmospheric
correction methods in GPro which produce a radiance output,
the new methods divide out the effect of solar irradiance and
produce reflectance which is a surface property. A further
advantage of reflectances is that the image dynamics of the
different images in an image block is adjusted to match together.
Both models have the free variables flying and ground height as
well as view zenith and sun zenith angle. For a fast correction
the two heights and the sun zenith angle can be set constant.
The remaining view angle dependence results in a look-up-table
of correction constants A and B as defined in eqn. (6). The
ADS40 line scanner geometry allows a simple line by line
correction.
The BRDF correction reduces the intrinsic image gradients,
without removing image fluctuations and is the final step before
the image mosaicking. Remaining seams can then be removed
with conventional feathering. This is a step towards an
automatic generation of huge seamless maps.
6. OUTLOOK
In the current implementation the dark pixel value is determined
for each band separately. Using the geometric sensor model a
correlation of different bands can improve the selection result
and lead to a spectral classification.
For a better support of quantitative methods in remote sensing,
a step to a more accurate correction will be the integration of
topographic effects in atmospheric correction. The resulting
irradiance on the ground depends on slope and aspect of the
terrain, as well as the sky view factor for each point, i.e. the
fraction of the sky that is visible from the given point. This
needs integrating the geometric sensor model and an elevation
model in the radiometric correction and includes also non-local
effects, like shadowing from distant points.
Finally a class specific BRDF modelling would reflect the
individual differences in BRDF behaviour of ground surfaces.
This would assist a later classification and time series analysis.
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