Fernerkundung I (Digitale Bildverarbeitung) - Friedrich-Schiller ...

The Mosaic Area Collection panel also contains options for loading and saving the cut line
to or from a vector segment on a PCIDSK database. It is only possible to have a single
mosaic cut line per mosaic operation. However, it is possible to perform many mosaic
operations from one uncorrected image to one georeferenced image, each time selecting
a region with a different cut line. To do this, it is necessary to alternate between the
Mosaic Area Collection panel and the Disk to Disk Registration panel to collect cut lines,
and perform mosaics.
Blending:
Blending can be performed along seams between the georeferenced and uncorrected
images, making the seams unnoticeable. Cut lines can be hand-drawn or imported from
a vector segment. Blending makes the sharp changes occurring at the cut line appear
more gradual by altering pixel values at the cut line. The blend width sets the number of
pixels over which the blending will take place.
For example, if the blend width is eight, the values four pixels into the uncorrected image
from the cut line will be composed entirely of the original uncorrected image pixel value.
Similarly, the values four pixels into the georeferenced image from the cut line will be
composed entirely of the original georeferenced image pixel value. At the cut line, the
values will consist of 50% of the uncorrected image pixel values and 50% of the
georeferenced image pixel values. It is important to note that blending will not fix poor
registration problems. For instance, if a road does not match up well at a cut line, the
match up will be no better and may even be more obvious after blending is complete.
The blending width may be altered on the Disk to Disk Registration and Pre- Registration
Checking panels.
Color Balancing:
Uncorrected images can be altered to make the mosaic less noticeable. Color balancing is
achieved by calculating the lookup table required to approximately match the
uncorrected image to the georeferenced image. The creation of this new lookup table is
called histogram matching. An image histogram is a graph showing the number of pixels
with a given brightness, for each possible brightness value. In histogram matching, the
image histograms of the uncorrected and georeferenced images are compared, and an
attempt is made to make the uncorrected image histogram match the georeferenced
image histogram by creating a histogram matching lookup table. All values in the
uncorrected image will be passed through this lookup table to create the histogram
equalized (color balanced) image. The Color Matching panel in GCPWorks provides the
opportunity to select areas for histogram comparison. It is important that appropriate
selections are made. Like areas should be compared. Comparing bright fields to dark
mountains will produce a histogram equalized image with dark fields and very dark
mountains, or light mountains and very bright fields (depending on which is the
georeferenced and which is the uncorrected).
Further Reading: see GCPworks Users Guide.
3.7 ImageWorks – der stabile Image-Viewer aus den 90igern
ImageWorks ist ein recht flexibel verwendbarer und sehr stabiler Image Viewer mit
einigen Kanten und Haken in der Anwendung. So wird bereits beim Start die Anzahl der
ladbaren Kanäle und deren Auflösung bzw. deren Typ festgelegt. Dies ist nachträglich
nicht mehr veränderbar. Einige alte EASI/PACE Routinen arbeiten direkt mit dem Viewer
zusammen. Bilddaten in Imageworks können also „life“ verändert werden bzw. gesteuert
werden im Viewer durch Befehle in Xpace bzw. EASI. Das gesamte UserInterface wird
jedoch durch den FOCUS und die Algorithmenbibliothek abgelöst und ist daher nicht
mehr up-to-date und wird auch nicht mehr gepflegt – hier nur der Vollständigkeit wegen
aufgelistet.