|Main Objective: The Hyperspectral Imaging Network (HYPER-I-NET) is a four-year (2007-2010) FP6 Marie Curie Research Training Network designed to build an interdisciplinary European research community focusing on hyperspectral imaging activities.
Hyperspectral imaging is concerned with the measurement, analysis, and interpretation of spectra acquired from a given scene (or specific object) at a short, medium or long distance by an airborne or satellite imaging spectrometer. Hyperspectral sensors are now able to produce hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. Such wealth of spectral information has opened ground-breaking perspectives in many applications, including environmental and urban monitoring and assessment, target detection for military and homeland defense/security purposes, and risk prevention and response. The latter includes tracking wildfires, detecting biological threats, and monitoring oil spills and other types of chemical contamination.
The core strategy of HYPER-I-NET will be to create a powerful interdisciplinary synergy between different domains of expertise within Europe, and use it to break new grounds in areas related with hyperspectral imaging. This will be achieved by organizing a well structured multidisciplinary training programme that will cover all the different aspects that comprise the hyperspectral data processing chain, ranging from sensor design and flight operation to data collection, processing, interpretation, and dissemination. As a result, the theme of HYPER-I-NET is at the confluence of heterogeneous disciplines, such as sensor design and calibration, aerospace engineering, remote sensing, high performance computing, image/signal processing and Earth observation related products.
The main objectives of HYPER-I-NET will be to:
1. Bridge the gap between sensor design and hyperspectral data exploitation in remote sensing activities in Europe. This will be done by defining a so-called standard hyperspectral processing chain;
2. Develop standardized and innovative techniques/products for hyperspectral image analysis, taking into account specific requirements introduced by these data sets (collection, storage, processing and calibration);
3. Establish standardized data processing and validation/quality control procedures in all the steps of the hyperspectral processing chain;
4. Integrate knowledge from different disciplines (e.g., sensor design, data processing, computing, scientific applications) and their contribution to the development, operation and exploitation of hyperspectral imaging systems;
5. Improve the cooperation and transfer of knowledge (ToK), from Research Institutions, Universities and SMEs working on hyperspectral imaging;
6. Create a powerful multidisciplinary synergy that will allow a more solid integration of technical and scientific issues, building a true interdisciplinary network relying on standardization and joint terminology.
|Start Date: 01-01-2007|
|End Date: 01-01-2011|
|Team: José Manuel Bioucas Dias|
|Local Coordinator: José Manuel Bioucas Dias|