HORIZON 2020
Sparse Signal Processing Technologies For HyperSpectral Systems
Achievements
  1. Application Scenarios
  2. Design of hyperspectral sensors and camera systems
  3. Spectral Mosaic Data Recovery
  4. Spectral Mosaic Compression
  5. Robust blind source separation
  6. Hyperspectral image (HSI) unmixing
  7. Hyperspectral image clustering
  8. Multi-label Land Cover Classification
  9. Demonstration

PHySIS Integrated Processing Platform

Starting from the application scenarios detected likely to be impacted by PHySIS achievements and contextually considering the requirement specifications produced in WP2, a complete and detailed architectural design of the SW processing system has been produced.

Theoretical results and algorithms of all SW processing for the hyperspectral data are in the engineered system that integrates all of them. System enables validation and demonstration of results in terms of services, processing and performance, as well as the integration with the developed hardware system.

The engineered system is visible through the PHySIS Integrated Processing Platform that acts as the integration point of overall research and study activities to obtain a complete system that is useful to demonstrate functionalities, performances and proposed objectives in end-to-end configuration. It’s a complete system that starts from the acquired data as input to produce the products in output according to the user inputs as desiderata performances. The system is useful also and mainly for the promotion and dissemination activities in support to the business development of the team.

So the developments also focus on the user interface in terms of GUI and web services that we have develop according to design results. The design integrates all heterogeneous algorithms and techniques developed in the project by applications and functionalities. The main objective is to drive the user by a user-friendly selection of the activities and parameters to obtain the result as well as possible. The design will take care of quality metrics and metadata definitions regarding the quality of compression\decompression and other processing results. These outputs will contribute to further development of data payload unit designs based on these technologies.