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i.pansharpen - Image fusion algorithms to sharpen multispectral with high-res
panchromatic channels


imagery, fusion, sharpen, Brovey, IHS, HIS, PCA


i.pansharpen --help
i.pansharpen [-sl] red=name green=name blue=name pan=name output=basename method=string
[--overwrite] [--help] [--verbose] [--quiet] [--ui]

Serial processing rather than parallel processing

Rebalance blue channel for LANDSAT

Allow output files to overwrite existing files

Print usage summary

Verbose module output

Quiet module output

Force launching GUI dialog

red=name [required]
Name of raster map to be used for <red>

green=name [required]
Name of raster map to be used for <green>

blue=name [required]
Name of raster map to be used for <blue>

pan=name [required]
Name of raster map to be used for high resolution panchromatic channel

output=basename [required]
Name for output basename raster map(s)

method=string [required]
Method for pan sharpening
Options: brovey, ihs, pca
Default: ihs


i.pansharpen uses a high resolution panchromatic band from a multispectral image to
sharpen 3 lower resolution bands. The 3 lower resolution bands can then be combined into
an RGB color image at a higher (more detailed) resolution than is possible using the
original 3 bands. For example, Landsat ETM has low resolution spectral bands 1 (blue), 2
(green), 3 (red), 4 (near IR), 5 (mid-IR), and 7 (mid-IR) at 30m resolution, and a high
resolution panchromatic band 8 at 15m resolution. Pan sharpening allows bands 3-2-1 (or
other combinations of 30m resolution bands like 4-3-2 or 5-4-2) to be combined into a 15m
resolution color image.
i.pansharpen offers a choice of three different ’pan sharpening’ algorithms: IHS, Brovey,
and PCA.
For IHS pan sharpening, the original 3 lower resolution bands, selected as red, green and
blue channels for creating an RGB composite image, are transformed into IHS (intensity,
hue, and saturation) color space. The panchromatic band is then substituted for the
intensity channel (I), combined with the original hue (H) and saturation (S) channels, and
transformed back to RGB color space at the higher resolution of the panchromatic band. The
algorithm for this can be represented as: RGB -> IHS -> [pan]HS -> RGB.
With a Brovey pan sharpening, each of the 3 lower resolution bands and panchromatic band
are combined using the following algorithm to calculate 3 new bands at the higher
resolution (example for band 1):
new band1 = ----------------------- * panband
band1 + band2 + band3
In PCA pan sharpening, a principal component analysis is performed on the original 3 lower
resolution bands to create 3 principal component images (PC1, PC2, and PC3) and their
associated eigenvectors (EV), such that:
band1 band2 band3
PC1: EV1-1 EV1-2 EV1-3
PC2: EV2-1 EV2-2 EV2-3
PC3: EV3-1 EV3-2 EV3-3
PC1 = EV1-1 * band1 + EV1-2 * band2 + EV1-3 * band3 - mean(bands 1,2,3)
An inverse PCA is then performed, substituting the panchromatic band for PC1. To do this,
the eigenvectors matrix is inverted (in this case transposed), the PC images are
multiplied by the eigenvectors with the panchromatic band substituted for PC1, and mean of
each band is added to each transformed image band using the following algorithm (example
for band 1):
band1’ = pan * EV1-1 + PC2 * EV2-1 + PC3 * EV3-1 + mean(band1)
The assignment of the channels depends on the satellite. Examples of satellite imagery
with high resolution panchromatic bands, and lower resolution spectral bands include
Landsat 7 ETM, QuickBird, and SPOT.


The module currently only works for 8-bit images.
The command temporarily changes the computational region to the high resolution of the
panchromatic band during sharpening calculations, then restores the previous region
settings. The current region coordinates (and null values) are respected. The high
resolution panchromatic image is histogram matched to the band it is replaces prior to
substitution (i.e., the intensity channel for IHS sharpening, the low res band selected
for each color channel with Brovey sharpening, and the PC1 image for PCA sharpening).
By default, the command will attempt to employ parallel processing, using up to 3 cores
simultaneously. The -s flag will disable parallel processing, but does use an optimized
r.mapcalc expression to reduce disk I/O.
The three pan-sharpened output channels may be combined with d.rgb or r.composite. Colors
may be optionally optimized with i.colors.enhance. While the resulting color image will
be at the higher resolution in all cases, the 3 pan sharpening algorithms differ in terms
of spectral response.


Pan sharpening of a Landsat image from Boulder, Colorado, USA:
# R, G, B composite at 30m
g.region raster=p034r032_7dt20010924_z13_10 -p
d.rgb b=p034r032_7dt20010924_z13_10 g=lp034r032_7dt20010924_z13_20
# i.pansharpen with IHS algorithm
i.pansharpen red=p034r032_7dt20010924_z13_30 green=p034r032_7dt20010924_z13_20
blue=p034r032_7dt20010924_z13_10 pan=p034r032_7dp20010924_z13_80
output=ihs321 method=ihs
# display at 15m
g.region raster=ihs321_blue -p
d.rgb b=ihs321_blue g=ihs321_green r=ihs321_red

R, G, B composite of Landsat at 30m R, G, B composite of Brovey sharpened image at 15m

R, G, B composite of IHS sharpened image at 15m R, G, B composite of PCA sharpened image at 15m"

Example: LANDSAT ETM+ (Landsat 7), North Carolina sample dataset:
# original at 28m
g.region raster=lsat7_2002_10 -p
d.mon wx0
d.rgb b=lsat7_2002_10 g=lsat7_2002_20 r=lsat7_2002_30
# i.pansharpen with IHS algorithm
i.pansharpen red=lsat7_2002_30@PERMANENT \
green=lsat7_2002_20 blue=lsat7_2002_10 \
pan=lsat7_2002_80 method=ihs \
# display at 14.25m
g.region raster=lsat7_2002_ihs_red -p
d.rgb r=lsat7_2002_ihs_red g=lsat7_2002_ihs_green b=lsat7_2002_ihs_blue
# compare before/after (RGB support in "Advanced"):
# optionally color balancing:
i.colors.enhance r=lsat7_2002_ihs_red g=lsat7_2002_ihs_green b=lsat7_2002_ihs_blue

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