1i.colors.enhance(1) GRASS GIS User's Manual i.colors.enhance(1)
2
6 i.colors.enhance - Performs auto-balancing of colors for RGB images.
7
9 imagery, RGB, satellite, colors
10
12 i.colors.enhance
13 i.colors.enhance --help
14 i.colors.enhance [-fprs] red=name green=name blue=name
15 [strength=float] [--help] [--verbose] [--quiet] [--ui]
16 Flags:
18 -f
19 Extend colors to full range of data on each channel
20 -p
22 Preserve relative colors, adjust brightness only
23 -r
25 Reset to standard color range
26 -s
28 Process bands serially (default: run in parallel)
29 --help
31 Print usage summary
32 --verbose
34 Verbose module output
35 --quiet
37 Quiet module output
38 --ui
40 Force launching GUI dialog
41 Parameters:
43 red=name [required]
44 Name of red channel
45 green=name [required]
47 Name of green channel
48 blue=name [required]
50 Name of blue channel
51 strength=float
53 Cropping intensity (upper brightness level)
54 Options: 0-100
55 Default: 98
56
58 i.colors.enhance auto-balances and enhances the color channels of a RGB
59 image (e.g. from Landsat) to provide a more natural color mixture. Only
60 the color table of each image band is modified, the base data remains
61 untouched.
62 The module works by calculating a histogram for each color channel and
64 removing an adjustable amount of outliers from either end before recal‐
65 ibrating the color scale with r.colors.
66 It will work with any 8-bit RGB imagery set and the script is easily
68 modified to work with other datasets of greater band-depth.
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71 Depending on the image, it may or may not be advantageous to use the -p
72 flag to preserve the relative color scaling. You will have to experi‐
73 ment with the different options to find a setting that works best for
74 your particular imagery.
75 The strength option should generally be set in the 90-99 range. The
77 lower the number, the more saturated the image becomes. It represents
78 the percentage cut-off for the top end of the color histogram curve.
79 The lower end is fixed at 2% of the area under the curve.
80 For quicker execution of this module on large images you can achieve
82 largely similar results by switching to a coarser resolution before the
83 running of the module (using g.region) and then back to the original
84 resolution afterwards.
85
87 North Carolina sample dataset example with Landsat data:
88 g.region raster=lsat7_2002_10 -p
89 d.rgb blue=lsat7_2002_10 green=lsat7_2002_20 red=lsat7_2002_30
90 d.barscale at=55.3125,93.125 bcolor=white text_pos=over
91 i.colors.enhance blue=lsat7_2002_10 green=lsat7_2002_20 red=lsat7_2002_30 strength=95
92 d.rgb blue=lsat7_2002_10 green=lsat7_2002_20 red=lsat7_2002_30
93 d.barscale at=55.3125,93.125 bcolor=white text_pos=over
94 Uncorrected RGB composite of Landsat ETM channels B/G/R
95 Color corrected RGB composite of Landsat ETM channels B/G/R
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99 The strength option requires further refinement.
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102 d.rgb, g.region, i.oif, r.colors, r.composite, r.univar
103
105 Markus Neteler, Trento, Italy
106 M. Hamish Bowman, Dept. Marine Science, Otago University, New Zealand
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109 Available at: i.colors.enhance source code (history)
110 Accessed: Saturday Jan 21 21:17:01 2023
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117GRASS 8.2.1 i.colors.enhance(1)