#Radiometric Normalization of Multispectral Images Given two hyperspectral (more than visible electromagnetic frequencies) satallite images which concern the same area on the planetary surface, you will find that a significant amount of atmospheric noise detracts from your ability to determine the features on the surface that have indeed changed with time. With this program you can determine a.) the points in each which have the highest probability of NOT being changed and from that b.) how the images should look once noise has been filtered out. ##Required Packages
- Imad https://github.com/chipbuster/imad_R
- 2 hyperspectral satallite images (put the file paths in the main function)
- GDAL libraries, which can be acquired from the OSGEO website.
- You will also need the Eigen libraries. heavy lifting performance-wise goes on in radcal.cpp