[GRASSLIST:7609] Re: color balancing in mosaic

[Jonathan Greenberg]

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 at lynxseismicdata.com] 
Sent: Monday, July 18, 2005 3:10 PM
To: Hamish
Cc: jgreenberg at arc.nasa.gov; GRASSLIST at 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