Commit b53bc40d authored by Victor Poughon's avatar Victor Poughon

DOC: review recipe residual registration

parent d6662e0e
Pipeline #1740 passed with stages
in 48 minutes and 31 seconds
......@@ -29,7 +29,7 @@ register two images. This process can be easily extended to perform
image series registration.
The aim of this example is to describe how to register a Level 1
QuickBird image over an orthorectify Pleiades image over the area of
QuickBird image over an orthorectified Pleiades image over the area of
Toulouse, France.
|image1| |image2|
......@@ -40,35 +40,30 @@ Extract metadata from the image reference
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
We first dump geometry metadata of the image we want to refine in a text
file. In OTB, we use the extension *.geom* for this type of file. As you
will see the application which will estimate a refine geometry only
file. In OTB, we use the extension *.geom* for this type of file.
The application to estimate a refined geometry only
needs as input this metadata and a set of homologous points. The
refinement application will create a new *.geom* file containing refined
geometry parameters which can be used after for reprojection for
example.
The use of external *.geom* file is available in OTB since release
:math:`3.16`. See
`here <http://wiki.orfeo-toolbox.org/index.php/ExtendedFileName>`__ for
more information.
External *.geom* files can also be used with :ref:`extended filenames<extended-filenames>`.
::
otbcli_ReadImageInfo -in slave_image
-outkwl TheGeom.geom
otbcli_ReadImageInfo -in slave_image
-outkwl TheGeom.geom
Extract homologous points from images
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The main idea of the residual registration is to estimate an second
The main idea of the residual registration is to estimate a second
transformation (after the application of sensors model).
The homologous point application uses an interest point detection method to
get a set of points with matches in both images.
The homologous point application use interest point detection method to
get a set of point which match in both images.
The basic idea is to use this set of homologous points and estimate with
them a residual transformation between the two images.
The basic idea is to use this set of homologous points to estimate
a residual transformation between the two images.
There is a wide variety of keypoint detectors in the literature, and they
allow for the detection and description of local features in images. These algorithms
......
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