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PROGRAM:

NAME


i.colors.enhance - Performs auto-balancing of colors for RGB images.

KEYWORDS


imagery, RGB, satellite, colors

SYNOPSIS


i.colors.enhance
i.colors.enhance --help
i.colors.enhance [-fprs] red=name green=name blue=name [strength=float] [--help]
[--verbose] [--quiet] [--ui]

Flags:
-f
Extend colors to full range of data on each channel

-p
Preserve relative colors, adjust brightness only

-r
Reset to standard color range

-s
Process bands serially (default: run in parallel)

--help
Print usage summary

--verbose
Verbose module output

--quiet
Quiet module output

--ui
Force launching GUI dialog

Parameters:
red=name [required]
Name of red channel

green=name [required]
Name of green channel

blue=name [required]
Name of blue channel

strength=float
Cropping intensity (upper brightness level)
Options: 0-100
Default: 98

DESCRIPTION


i.colors.enhance auto-balances and enhances the color channels of a RGB image (e.g. from
Landsat) to provide a more natural color mixture. Only the color table of each image band
is modified, the base data remains untouched.

The module works by calculating a histogram for each color channel and removing an
adjustable amount of outliers from either end before recalibrating the color scale with
r.colors.

It will work with any 8-bit RGB imagery set and the script is easily modified to work with
other datasets of greater band-depth.

NOTES


Depending on the image, it may or may not be advantageous to use the -p flag to preserve
the relative color scaling. You will have to experiment with the different options to find
a setting that works best for your particular imagery.

The strength option should generally be set in the 90-99 range. The lower the number, the
more saturated the image becomes. It represents the percentage cut-off for the top end of
the color histogram curve. The lower end is fixed at 2% of the area under the curve.

For quicker execution of this module on large images you can achieve largely similar
results by switching to a coarser resolution before the running of the module (using
g.region) and then back to the original resolution afterwards.

EXAMPLE


North Carolina sample dataset example with Landsat data:
g.region raster=lsat7_2002_10 -p
d.rgb blue=lsat7_2002_10 green=lsat7_2002_20 red=lsat7_2002_30
d.barscale at=55.3125,93.125 bcolor=white text_pos=over
i.colors.enhance blue=lsat7_2002_10 green=lsat7_2002_20 red=lsat7_2002_30 strength=95
d.rgb blue=lsat7_2002_10 green=lsat7_2002_20 red=lsat7_2002_30
d.barscale at=55.3125,93.125 bcolor=white text_pos=over
Uncorrected RGB composite of Landsat ETM channels B/G/R

Color corrected RGB composite of Landsat ETM channels B/G/R

TODO


The strength option requires further refinement.

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