Calculates the continuum-removed signature of a hyperspectral spectrum (see e.g., http://speclab.cr.usgs.gov/PAPERS/tetracorder/, Figure 1A). We first locate the concave inflection points in the spectrum and connect them via straight line segments, forming the initial approximation to the continuum. Next we locate the bands for which this piecewise linear function underestimates the band's reflectance value, and add those bands to the continuum.
Once the continuum is estimated, the continuum-removed representation is calculated according to:
cr[i] = spectrum[i]/continuum[i]
where spectrum is the input spectrum, continuum is the estimated
continuum, and i is the index of the ith band.
- OSX 10.6+
- gcc 4.0+
To build the demo program "cr" just run "make".
The cr program takes an input file of the following format:
[N]
[band 1 wavelength] [band 1 DN]
... ...
[band N wavelength] [band N DN]
and produces an output file of the following format:
[N]
[band 1 wavelength] [band 1 DN] [band 1 CR] [band 1 CC]
... ... ... ...
[band N wavelength] [band N DN] [band N CR] [band N CC]
where
[band i DN] = value of the original spectrum at band i
[band i CR] = value of the continuum-removed spectrum at band i
[band i CC] = value of the estimated continuum at band i
To test the "cr" program with an example spectrum, run:
cr example/cidat.txt
This will produce the output file "crdat.txt" of the format given above.
- Python 2.6
- numpy 1.6.1
- swig
- numpy.i (http://docs.scipy.org/doc/numpy/reference/swig.interface-file.html)
- matplotlib (optional, for plotting spectra)
The command
python setup.py build
will build the _lincr.so library in the build/(architecture)/
directory.
The cr.py program is an example wrapper for the lincr library. To try it, run the command:
python cr.py -i example/cidat.txt -p -v
The format of the example/cidat.txt file are provided in README_C.txt
- Matlab 2011a+
Run the lincr.m wrapper after building the standalone (C) version.
Please cite the following paper if you publish any works using this code:
B. D. Bue, E. Merényi, and B. Csathó, “Automated Labeling of Materials in Hyperspectral Imagery,” IEEE Trans. on Geoscience and Remote Sensing, vol. 48, no. 11, pp. 4059–4070, 2010.
If you receive CR values > 1, try reducing the value of the DIFFEPS variable in lincr.c.
Please contact the author (bbue@alumni.rice.edu) if you have any questions regarding this program.