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

AUTOMOS
Automosaic, can be used to automatically mosaic georeferenced
Image databases that have the same georeferencing. This is the
Most powerfull solution for full automatic mosaic generation. Output
Is created automatically. Two very important subfunctions are
included:
TREMOV (trend removal) can be used to radiometrically balance big
mosaics removing trends or hot spots in an image using APOLY2
and FPOLY2.
RBAL (radiometrical balancing) calculates Lookup table balancing for
each scene to make the adjacent scenes match better. Resulting
mosaics show less patchiness (RADNORM Programm).
With the MOSTYP function the cutline can be adjusted to areas that
show similar DNs – optimal cutline calculation (“Cutline”) can be
adjusted using different cost functions (CFUNC).
However, AUTOMOS is a complex routine and sometimes fails to
complete the mosaicing process.
MOSAIC
IMERGE.eas
MATCH
CREMOS.EAS
Image Mosaicking, Moves image data from an input image database
file to an output image database file. The mosaicking process may
be controlled by a vector segment defining the mosaic cut-line. In
addition, the input image database data may be modified by a
lookup table before it is moved to the output database.
Merge Image Files Merges one image channel from one or more
image files to produce one output file. IMERGE overwrites one input
image file with the next input file, all within the output file
Histogram Matching LUT Creates a lookup table which performs
histogram matching of an input image to a master image. The
output lookup table is saved on the input database and can be used
by program LUT to modify input image.
Mosaicing EASI routine.
Noise removal:
LRP
DSTRIPE
Line Replacement
Image Destriping
Frequency transforms:
FTF
FTI
FFREQ
Fourier Transformation
Inverse Fourier Transformation
Freq Domain Filter
Database Image Filtering:
FAV
FED
FEFROST
Averaging (Mean) Filter Performs AVERAGE filtering on image data.
The Averaging (mean) filter smooths image data, eliminating noise.
Edge Detection Filter (up to 33x33) Performs EDGE DETECTION
filtering for Image data. The edge detection filter creates an image
where edges (sharp changes in grey-level values) are shown.
Enhanced Frost Filtering (up to 33x33), FEFROST performs
enhanced frost filtering on any type of image data. The filter is
primarily used on radar data to remove high frequency noise
(speckle) while preserving high frequency features (edges).