HyperMix: An open source tool for hyperspectral imaging
Spectral unmixing has been a popular technique for analyzing remotely sensed hyperspectral images. The goal of unmixing is to find a collection of pure spectral signatures (called endmembers) that can explain each (possibly mixed) pixel of the scene as a combination of endmembers, weighted by their coverage fractions in the pixel or abundances. Over the last years, many algorithms have been presented to address the different parts of the spectral unmixing chain. These algorithms can be categorized in estimation of the number of end-members, identification of the endmember signatures, and estimation of the endmember's abundances on each pixel. This work presents a tool that integrates many efficient implementations of different methods in order to build more complex processing graphical chains. Also, the tool offers compatibility with the graphical processing unit (GPU), so that algorithms are automatically executed in parallel by the GPU (if available) in order to improve performance. The tool is available online from http://hypercomphypermix.blogspot.com.es and has been validated with both synthetic and real hyper-spectral scenes providing state-of-the-art unmixing results.