Hi, There,
I have problem to do color balancing for a mosaiced composited landsat TM
images. There are 4 images, they have difference in colors. I used r.blend, 3
of the image colorr are close now. But the 4th image have a very big
difference in color tone with other 3, it seems r.blend does not work for it.
Do you have a better way for this? I am running GRASS6.0 now. Please help!!
Thanks!!
Feng Tan
Feng:
Are you going to be performing classification on these mosaicked images, or
are you just making a graphic for a presentation? There's an important
distinction between making a "nice picture" and doing correct image-to-image
registration for mapping purposes, which is why I ask...
--j
On 7/15/05 6:42 AM, "Feng Tan" <feng@lynxseismicdata.com> wrote:
Hi, There,
I have problem to do color balancing for a mosaiced composited landsat TM
images. There are 4 images, they have difference in colors. I used r.blend, 3
of the image colorr are close now. But the 4th image have a very big
difference in color tone with other 3, it seems r.blend does not work for it.
Do you have a better way for this? I am running GRASS6.0 now. Please help!!Thanks!!
Feng Tan
--
Jonathan A. Greenberg, PhD
NRC Research Associate
NASA Ames Research Center
MS 242-4
Moffett Field, CA 94035-1000
650-604-5896
AIM: jgrn307
MSN: jgrn307@hotmail.com
Hi, Jonathan,
Thank you very much for your reply!! Yes, I only use the mosaiced images for
"good looking" not for classification purpose. (I know it takes raw image for
classification, so we don't change their spectral information, thanks for
remind me this!). I believe you have ideas how to color balancing for my
mosaiced, color composited landsat images for viewing.
Have a nice weekend!!
Feng
On Friday 15 July 2005 14:35, you wrote:
Feng:
Are you going to be performing classification on these mosaicked images, or
are you just making a graphic for a presentation? There's an important
distinction between making a "nice picture" and doing correct
image-to-image registration for mapping purposes, which is why I ask...--j
On 7/15/05 6:42 AM, "Feng Tan" <feng@lynxseismicdata.com> wrote:
> Hi, There,
>
> I have problem to do color balancing for a mosaiced composited landsat TM
> images. There are 4 images, they have difference in colors. I used
> r.blend, 3 of the image colorr are close now. But the 4th image have a
> very big difference in color tone with other 3, it seems r.blend does not
> work for it. Do you have a better way for this? I am running GRASS6.0
> now. Please help!!
>
> Thanks!!
>
> Feng Tan
Thank you very much for your reply!! Yes, I only use the mosaiced
images for "good looking" not for classification purpose. (I know it
takes raw image for classification, so we don't change their spectral
information, thanks for remind me this!). I believe you have ideas
how to color balancing for my mosaiced, color composited landsat
images for viewing.
I am no RS expert, but for nice looking LANDSAT output here are some
things you might try.
Use d.histogram to do a subjective or r.stats to do an objective
analysis of each band's distribution. Rescale with r.rescale or
r.rescale.eq (?) and gate filter back to (0,255) with r.mapcalc.
Or try r.univar and resample to +/- 1.5 stdev's from the mean or
whatever is appropriate.
Then use i.oif to see which combination of three bands show the most
information and try displaying different RGB combinations of those three
bands with d.rgb & see what looks good.
Hamish
Hi, Hamish,
Thanks for give me ideas! I use i.fusion.brovey to sharppen the image to 15m
resolution first, then adjust the color from brovey's RGB channels according
a reference image in the mosaic. I am trying your idea, but it doesn't work
very well, at least it does not process automatically. It is hard to choose
the proper min, max from histogram. Maybe I should do more testing. Any more
suggestion?
Feng
On Sunday 17 July 2005 20:36, you wrote:
> Thank you very much for your reply!! Yes, I only use the mosaiced
> images for "good looking" not for classification purpose. (I know it
> takes raw image for classification, so we don't change their spectral
> information, thanks for remind me this!). I believe you have ideas
> how to color balancing for my mosaiced, color composited landsat
> images for viewing.I am no RS expert, but for nice looking LANDSAT output here are some
things you might try.Use d.histogram to do a subjective or r.stats to do an objective
analysis of each band's distribution. Rescale with r.rescale or
r.rescale.eq (?) and gate filter back to (0,255) with r.mapcalc.
Or try r.univar and resample to +/- 1.5 stdev's from the mean or
whatever is appropriate.Then use i.oif to see which combination of three bands show the most
information and try displaying different RGB combinations of those three
bands with d.rgb & see what looks good.Hamish
Feng:
The "official" way you can do this (this will work for "true"
radiometric normalization so, by definition, will work for the "photo"
normalization) is using image-to-image empirical line. Here's the basic
idea (I have no idea how to do this in GRASS, by the way, maybe someone can
translate these instructions into GRASS capabilities or, if any programmers
are interested, I can help direct the development of an add-on to GRASS):
1) Make sure your images are georegistered to one another (they should be if
you want to mosaick anyway).
2) Pick 10-50 locations of varying brightness in the overlap regions between
two images.
3) Choose one of the two images as the "reference image". I'll refer to the
other overlapping image as the uncalibrated image.
4) For each band (in your case, probably R G B), do a linear regression
between reference image pixels and the corresponding uncalibrated image
pixels.
5) (Optional) Remove any outliers in the analysis.
6) You now have a slope and offset coefficient that you can apply to the
uncalibrated image which will now radiometrically register this with the
reference image.
Voila!
--j
-----Original Message-----
From: Feng Tan [mailto:feng@lynxseismicdata.com]
Sent: Monday, July 18, 2005 3:10 PM
To: Hamish
Cc: jgreenberg@arc.nasa.gov; GRASSLIST@baylor.edu
Subject: Re: [GRASSLIST:7563] Re: color balancing in mosaic
Hi, Hamish,
Thanks for give me ideas! I use i.fusion.brovey to sharppen the image to 15m
resolution first, then adjust the color from brovey's RGB channels according
a reference image in the mosaic. I am trying your idea, but it doesn't work
very well, at least it does not process automatically. It is hard to choose
the proper min, max from histogram. Maybe I should do more testing. Any
more
suggestion?
Feng
On Sunday 17 July 2005 20:36, you wrote:
> Thank you very much for your reply!! Yes, I only use the mosaiced
> images for "good looking" not for classification purpose. (I know it
> takes raw image for classification, so we don't change their spectral
> information, thanks for remind me this!). I believe you have ideas
> how to color balancing for my mosaiced, color composited landsat
> images for viewing.I am no RS expert, but for nice looking LANDSAT output here are some
things you might try.Use d.histogram to do a subjective or r.stats to do an objective
analysis of each band's distribution. Rescale with r.rescale or
r.rescale.eq (?) and gate filter back to (0,255) with r.mapcalc.
Or try r.univar and resample to +/- 1.5 stdev's from the mean or
whatever is appropriate.Then use i.oif to see which combination of three bands show the most
information and try displaying different RGB combinations of those three
bands with d.rgb & see what looks good.Hamish
Hi, Guys,
I am very interested in developing the tool for color balancing in GRASS.
Jonathan's ideas make sense that uses overlapping information of the images,
but it only considered a few sampling areas, plus the regression part
involves the R/Grass interface which I haven't get my computer works yet. I
am thinking about combine Hamish's histogram idea with Jonathan's overlapping
ideas together. That is:
1) d.histogram for both images (for example, R channel) in the overlapping
area
2) r.rescale the histogram of the image according to the reference image in
the overlapping area.
3) apply the modified histogram to the entire images (I don't know how to do
this in GRASS6.0 ,maybe r.rescale again? ). In this step, some cell values
are changed if they exist in the overlapping area, some cell values will not
change if they don't exist in the overlapping area.
Please tell me if this makes sense?
Thanks,
Feng
On Monday 18 July 2005 16:18, you wrote:
Feng:
The "official" way you can do this (this will work for "true"
radiometric normalization so, by definition, will work for the "photo"
normalization) is using image-to-image empirical line. Here's the basic
idea (I have no idea how to do this in GRASS, by the way, maybe someone can
translate these instructions into GRASS capabilities or, if any programmers
are interested, I can help direct the development of an add-on to GRASS):1) Make sure your images are georegistered to one another (they should be
if you want to mosaick anyway).
2) Pick 10-50 locations of varying brightness in the overlap regions
between two images.
3) Choose one of the two images as the "reference image". I'll refer to
the other overlapping image as the uncalibrated image.
4) For each band (in your case, probably R G B), do a linear regression
between reference image pixels and the corresponding uncalibrated image
pixels.
5) (Optional) Remove any outliers in the analysis.
6) You now have a slope and offset coefficient that you can apply to the
uncalibrated image which will now radiometrically register this with the
reference image.Voila!
--j
-----Original Message-----
From: Feng Tan [mailto:feng@lynxseismicdata.com]
Sent: Monday, July 18, 2005 3:10 PM
To: Hamish
Cc: jgreenberg@arc.nasa.gov; GRASSLIST@baylor.edu
Subject: Re: [GRASSLIST:7563] Re: color balancing in mosaicHi, Hamish,
Thanks for give me ideas! I use i.fusion.brovey to sharppen the image to
15mresolution first, then adjust the color from brovey's RGB channels
accordinga reference image in the mosaic. I am trying your idea, but it doesn't work
very well, at least it does not process automatically. It is hard to choose
the proper min, max from histogram. Maybe I should do more testing. Any
more
suggestion?Feng
On Sunday 17 July 2005 20:36, you wrote:
> > Thank you very much for your reply!! Yes, I only use the mosaiced
> > images for "good looking" not for classification purpose. (I know it
> > takes raw image for classification, so we don't change their spectral
> > information, thanks for remind me this!). I believe you have ideas
> > how to color balancing for my mosaiced, color composited landsat
> > images for viewing.
>
> I am no RS expert, but for nice looking LANDSAT output here are some
> things you might try.
>
> Use d.histogram to do a subjective or r.stats to do an objective
> analysis of each band's distribution. Rescale with r.rescale or
> r.rescale.eq (?) and gate filter back to (0,255) with r.mapcalc.
> Or try r.univar and resample to +/- 1.5 stdev's from the mean or
> whatever is appropriate.
>
>
> Then use i.oif to see which combination of three bands show the most
> information and try displaying different RGB combinations of those three
> bands with d.rgb & see what looks good.
>
>
>
> Hamish
Histogram matching is certainly another technique you can use. The problem
with histogram matching arises when your scenes have drastically different
scene components (so the histograms shouldn't match anyway). Most
differences between two images are not as complex as requiring the
application of a probability distribution, rather just modifying the gain
and offset (the differences are almost always linear). The empirical line
technique can be applied in a semi- or fully automated way, and does not
have any real restriction short of requiring the two images to overlap.
--j
On 7/20/05 9:58 AM, "Feng Tan" <feng@lynxseismicdata.com> wrote:
Hi, Guys,
I am very interested in developing the tool for color balancing in GRASS.
Jonathan's ideas make sense that uses overlapping information of the images,
but it only considered a few sampling areas, plus the regression part
involves the R/Grass interface which I haven't get my computer works yet. I
am thinking about combine Hamish's histogram idea with Jonathan's overlapping
ideas together. That is:1) d.histogram for both images (for example, R channel) in the overlapping
area
2) r.rescale the histogram of the image according to the reference image in
the overlapping area.
3) apply the modified histogram to the entire images (I don't know how to do
this in GRASS6.0 ,maybe r.rescale again? ). In this step, some cell values
are changed if they exist in the overlapping area, some cell values will not
change if they don't exist in the overlapping area.Please tell me if this makes sense?
Thanks,
Feng
On Monday 18 July 2005 16:18, you wrote:Feng:
The "official" way you can do this (this will work for "true"
radiometric normalization so, by definition, will work for the "photo"
normalization) is using image-to-image empirical line. Here's the basic
idea (I have no idea how to do this in GRASS, by the way, maybe someone can
translate these instructions into GRASS capabilities or, if any programmers
are interested, I can help direct the development of an add-on to GRASS):1) Make sure your images are georegistered to one another (they should be
if you want to mosaick anyway).
2) Pick 10-50 locations of varying brightness in the overlap regions
between two images.
3) Choose one of the two images as the "reference image". I'll refer to
the other overlapping image as the uncalibrated image.
4) For each band (in your case, probably R G B), do a linear regression
between reference image pixels and the corresponding uncalibrated image
pixels.
5) (Optional) Remove any outliers in the analysis.
6) You now have a slope and offset coefficient that you can apply to the
uncalibrated image which will now radiometrically register this with the
reference image.Voila!
--j
-----Original Message-----
From: Feng Tan [mailto:feng@lynxseismicdata.com]
Sent: Monday, July 18, 2005 3:10 PM
To: Hamish
Cc: jgreenberg@arc.nasa.gov; GRASSLIST@baylor.edu
Subject: Re: [GRASSLIST:7563] Re: color balancing in mosaicHi, Hamish,
Thanks for give me ideas! I use i.fusion.brovey to sharppen the image to
15mresolution first, then adjust the color from brovey's RGB channels
accordinga reference image in the mosaic. I am trying your idea, but it doesn't work
very well, at least it does not process automatically. It is hard to choose
the proper min, max from histogram. Maybe I should do more testing. Any
more
suggestion?Feng
On Sunday 17 July 2005 20:36, you wrote:
Thank you very much for your reply!! Yes, I only use the mosaiced
images for "good looking" not for classification purpose. (I know it
takes raw image for classification, so we don't change their spectral
information, thanks for remind me this!). I believe you have ideas
how to color balancing for my mosaiced, color composited landsat
images for viewing.I am no RS expert, but for nice looking LANDSAT output here are some
things you might try.Use d.histogram to do a subjective or r.stats to do an objective
analysis of each band's distribution. Rescale with r.rescale or
r.rescale.eq (?) and gate filter back to (0,255) with r.mapcalc.
Or try r.univar and resample to +/- 1.5 stdev's from the mean or
whatever is appropriate.Then use i.oif to see which combination of three bands show the most
information and try displaying different RGB combinations of those three
bands with d.rgb & see what looks good.Hamish
--
Jonathan A. Greenberg, PhD
NRC Research Associate
NASA Ames Research Center
MS 242-4
Moffett Field, CA 94035-1000
650-604-5896
AIM: jgrn307
MSN: jgrn307@hotmail.com