HypeRvieW: an open source desktop application for hyperspectral remote-sensing data processing

In this paper, we present a desktop application for the analysis, reference data generation, registration and supervised spatial-spectral classification of hyperspectral remote sensing images through a simple and intuitive interface. Regarding the classification ability, the different classification schemes are implemented by using a chain structure as a base. It consists of five configurable stages that must be executed in fixed order: preprocessing, spatial processing, pixel-wise classification, combination and postprocessing. The modular implementation makes its extension easy by adding new algorithms for each stage or new classification chains. The tool has been designed as a platform which is open to the incorporation of algorithms by the users interested in comparing classification schemes. As an example of use a classification scheme based on the Quick Shift (QS) algorithm for segmentation and on Extreme Learning Ma- chines (ELM) or Support Vector Machines (SVMs) for classification is also proposed. The application is license-free, runs on the Linux operating system and was developed in C language using the GTK library, as well as other free libraries to build the graphical user interfaces.

keywords: desktop tool, remote sensing, classification, registration, hyperspectral data