Hi,
I have got 485 8-bit TIFF ortophotos that I would like to merge in a unique image or maybe 3 to 5 images. The procedure I used was r.in.gdal --> r.patch - NO PROBLEM WITH THAT. The problem is that the images are not of a very good quality and have very different values for the same land class, i.e. some are darker and some lighter + they are shot at different times of the day (hilly region). That means the shadows extend differently.
To get a better view of the area I tried to use r.colors col=grey.eq, but the edges of the original images are still very visible. Then I thought about i.gray.scale. As I understood i.gray.scale changes the values in the image. In that way I would manage to get together the images with the values much more alike.
But there is no command like that any more. ???
Any better idea? I am not really and expert in image analysis. The aim is to transform the images in a way the same values would indicate the same land classes. After that get some spectral signatures and try to classify the image in a more or less correct way.
If anything is not clear enough, please ask for clarification.
Thanks, Miha Staut
_________________________________________________________________
Help STOP SPAM with the new MSN 8 and get 2 months FREE* http://join.msn.com/?page=features/junkmail
Miha STAUT wrote:
I have got 485 8-bit TIFF ortophotos that I would like to merge in a unique
image or maybe 3 to 5 images. The procedure I used was r.in.gdal --> r.patch
- NO PROBLEM WITH THAT. The problem is that the images are not of a very
good quality and have very different values for the same land class, i.e.
some are darker and some lighter + they are shot at different times of the
day (hilly region). That means the shadows extend differently.
To get a better view of the area I tried to use r.colors col=grey.eq, but
the edges of the original images are still very visible. Then I thought
about i.gray.scale. As I understood i.gray.scale changes the values in the
image. In that way I would manage to get together the images with the values
much more alike.
But there is no command like that any more. ???
r.colors alone won't help, because it only changes the colour table,
which isn't used by r.patch.
However, you could use r.colors followed by:
r.mapcalc 'output = #input'
to replace each cell's value with its intensity level from the colour
table.
Any better idea? I am not really and expert in image analysis. The aim is to
transform the images in a way the same values would indicate the same land
classes. After that get some spectral signatures and try to classify the
image in a more or less correct way.
If relief shading is an issue, you could try using shade.rel.sh on a
DEM to compute the expected illumination, then computing the ratios.
That assumes that you can figure out how to transform either the DEM
or the computed intensity map to match the orthophoto.
--
Glynn Clements <glynn.clements@virgin.net>
On Tue, Dec 09, 2003 at 01:43:00PM +0000, Miha STAUT wrote:
Hi,
I have got 485 8-bit TIFF ortophotos that I would like to merge in a unique
image or maybe 3 to 5 images. The procedure I used was r.in.gdal --> r.patch
- NO PROBLEM WITH THAT. The problem is that the images are not of a very
good quality and have very different values for the same land class, i.e.
some are darker and some lighter + they are shot at different times of the
day (hilly region). That means the shadows extend differently.
To get a better view of the area I tried to use r.colors col=grey.eq, but
the edges of the original images are still very visible. Then I thought
about i.gray.scale. As I understood i.gray.scale changes the values in the
image. In that way I would manage to get together the images with the values
much more alike.
But there is no command like that any more. ???
Any better idea? I am not really and expert in image analysis. The aim is to
transform the images in a way the same values would indicate the same land
classes. After that get some spectral signatures and try to classify the
image in a more or less correct way.
If anything is not clear enough, please ask for clarification.
Thanks, Miha Staut
Probably you need (to implement) "histogram matching":
calculating an overall histogram from the individual histograms, then
modify all individual histograms to that overall histogram.
I would need that functionality as well 
Here is some ref (googled):
http://www.cnr.berkeley.edu/~bingxu/geo7366/Lecture10/HistogramAdjust.pdf
Markus