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
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.
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.
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
The
strength option requires further refinement.
d.rgb,
g.region,
i.oif,
r.colors,
r.composite,
r.univar
Markus Neteler, Trento, Italy
M. Hamish Bowman, Dept. Marine Science, Otago University, New Zealand
SOURCE CODE
Available at:
i.colors.enhance source code
(history)
Latest change: Thursday Jul 04 18:40:36 2024 in commit: d880ec0a6d88ce64a10f18c7d3e8701bf8e8972f
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GRASS Development Team,
GRASS GIS 8.5.0dev Reference Manual