DESCRIPTION

i.fusion.hpf combines high-resolution panchromatic data with lower resolution multispectral data, resulting in an output with both excellent detail and a realistic representation of original multispectral scene colors. The process involves a convolution using a High Pass Filter (HPF) on the high resolution data, then combining this with the lower resolution multispectral data. Read the description of the Algorithm below.

    Some formula +++

The algorithm's steps are: 1. Read pixel sizes from Image files and calculate R, the ratio of multispectral cell size to high-resolution cell size 2. Apply the High-pass filter to the high spatial resolution image. 3. Resample the Multi-Spectral image to the pixel size of the high-pass image. Note, bilinear resampling required (4 nearest neighbours)! 4. Add the HPF image weighted relative to the global standard deviation of the Multi-Spectral band. 5. Optionally, stretch linearly the new HPF-Sharpened image to match the mean and standard deviation of the input Multi-Sectral image.

NOTES

The command changes temporarily to the high resolution of the panchromatic image for creating the sharpened image, then restores the previous region settings. The current region coordinates are respected. Pan-sharpened images may be combined with d.rgb or r.composite.

EXAMPLE

HPFA-based fusion of satellite imagery... : *** Fix Below ***

g.region rast= -p

# R, G, B composite at 28.5m 
d.rgb b=lsat7_2002_10 g=lsat7_2002_20 r=lsat7_2002_30

# Brovey fusion
i.fusion.brovey -l ms1=lsat7_2002_20 ms2=lsat7_2002_40 \
                   ms3=lsat7_2002_50 pan=lsat7_2002_80 \
                   outputprefix=brovey

# display at 14.25m
g.region rast=brovey.blue -p
d.rgb b=brovey.blue g=brovey.green r=brovey.red

Results:

R, G, B composite of Landsat at 28.5m

R, G, B composite of Landsat Brovey fusion at 14.25m

Colors may be optionally optimized.

REFERENCES

Original Brovey formula reference unknown, probably
Roller, N.E.G. and Cox, S., 1980. Comparison of Landsat MSS and merged MSS/RBV data for analysis of natural vegetation. Proc. of the 14th International Symposium on Remote Sensing of Environment, San Jose, Costa Rica, 23-30 April, pp. 1001-1007
Pohl, C., and J.L. van Genderen, 1998. Multisensor image fusion in remote sensing: concepts, methods and application. Int. J. of Rem. Sens., 19, 823-854.
M. Neteler, D. Grasso, I. Michelazzi, L. Miori, S. Merler, and C. Furlanello, 2005. An integrated toolbox for image registration, fusion and classification. International Journal of Geoinformatics, 1(1):51-61 (PDF)

AUTHOR

Markus Neteler, ITC-irst, Italy

Last changed: $Date: 2011-11-08 11:42:51 +0200 (Tue, 08 Nov 2011) $

DESCRIPTION

NOTES

EXAMPLE

SEE ALSO

REFERENCES

AUTHOR