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Nearest Regularized Subspace (NRS) Classifier

Introduction

The NRS classifier is a supervised classification technique first proposed in

W. Li, E. W. Tramel, S. Prasad, and J. E. Fowler, "Nearest Regularized Subspace for Hyperspectral Classification," IEEE Transactions on Geoscience and Remote Sensing, accepted October, 2012.

This code is shared as a living work. It is our intent to add functionality, fix bugs, and address any other potential concerns through this repository.

Additionally, it is our hope that this repository will serve to promote reproducibility in research. If you're researching the topic, please feel free to fork us and build up new functionality!

Langauges

The NRS classifier is currently implemented in Matlab. This choice of language is more an artifact of our research work-flow than of any particular desire to choose Matlab over any other implementation. While Matlab is easy for us, many do not have access to this piece of proprietary software.

Future plans include ports to other familiar script-style languages, such as Octave and Python, to allow for free and open use of this software. If you have a desire or inclination to port this code to your favorite language, please submit a pull request and we'll build up a ports section.