Tools for hyperspectral imaging
Documentation at 2015-01-15.
Hyperspectral imaging is used to visualize chemistry, the spatial relation between chemicals and the proportion of them. PySptools is a python module that implements spectral and hyperspectral algorithms. Specializations of the library are the endmembers extraction, unmixing process, supervised classification, target detection, noise reduction, convex hull removal and features extraction at spectrum level. The library is designed to be easy to use and almost all functionality has a plot function to save you time with the data analysis process. The actual sources of the algorithms are the Matlab Hyperspectral Toolbox of Isaac Gerg, the pwctools of M. A. Little, the Endmember Induction Algorithms toolbox (EIA) and the HySime Matlab module of José Bioucas-Dias and José Nascimento. You can download PySptools from the PySptools Project Page hosted by Sourceforge.net or from the pypi packages repository.
A simple comparaison between ATGP and NFINDR.
Methanol gas synthetic images made by unmixing. The data used for the demonstration is acquired with a Telops Hyper-Cam instrument.
Quartz classification of a drill core datacube. The data used for the demonstration is acquired with a Telops Hyper-Cam instrument.
Smokestack effluents analysis. The data used for the demonstration is acquired with a Telops Hyper-Cam instrument.
Some examples of convex hull removal and features extraction.
Following examples use the IPython Notebook.
Summary of functions and classes by modules