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ISPRS-SI2017-TC3_WG4_Karantzalos_Report.pdf

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README.md

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 The HyRANK hyperspectral datasets has been developed in the framework of the ISPRS Scientific Initiatives. In particular, the “HyRANK Hyperspectral Satellite Dataset I” contains the openly available Hyperion hyperspectral dataset along with the corresponding reference/ ground truth data. The training set contains two hyperspectral images (i.e., Dioni and Loukia) and the validation set contains three hyperspectral images (i.e., Erato, Nefeli, Kiriki). The [HyRANK](http://www2.isprs.org/commissions/comm3/wg4/HyRANK.html) benchmark platform can be reached through the ISPRS website under [the Commission III](http://www2.isprs.org/commissions/comm3.html), [Working Group III/4](http://www2.isprs.org/commissions/comm3/wg4.html) ‘Hyperspectral Image Processing’ webpage.
 
+# Project
+
+_Name: Benchmark for Multi-platform Hyperspectral Image Processing_
+
+_Principle Investigator: Konstantinos Karantzalos, National Technical University of Athens, Greece_
+
+_Co-investigators: Eija Honkavaara, Finnish Geospatial Research Institute, Finland; Baoxin Hu, York University, Canada; Pölönen Ilkka, University of Jyväskylä, Finland; Zach. Kandylakis, Christos Kontopoulos, National Technical University of Athens, Greece_
+
+The ISPRS Scientific Initiative for a novel Benchmark on Multi-platform Hyperspectral Image Processing aims at promoting research and excellence on hyperspectral image processing through the efficient quantitative validation of state-of-the art techniques on hyperspectral datasets acquired from different satellite, airborne and UAVs acquisition platforms. The main goal is to fill the current gap regarding the limited availability of hyperspectral datasets and benchmarking frameworks for validating novel processing and data analytics methodologies against the state-of-the-art. To this end, the goal is to tackle these issues by: i) introducing novel, multi-platform hyperspectral imaging datasets as well as ii) introducing a benchmark framework for validating novel detection and classification algorithms. In particular, new datasets along with their corresponding ground truth will be gathered with different spatial and spectral resolution, acquired from different acquisition platforms. An online benchmarking framework will be also implemented for quantitatively comparing novel methodologies against the state-of-the-art.
+
+The final report is included.
+
+
 # Credits
 
+The original report for this project is available at the [ISPRS website](https://www.isprs.org/) and available at [this link](https://www.isprs.org/society/si/SI-2017/).
 The dataset was originally downloaded at the [Zenodo webpage](https://zenodo.org/records/1222202).
 
 To cite this dataset: