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Proceedings Paper

Survey and assessment of advanced feature extraction techniques and tools for EO applications
Author(s): Mikael Kamp Sorensen; Michael Schultz Rasmussen; Henning Skriver; Peter Johansen; Arthur Pece; Jesper Høyerup Thygesen
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Paper Abstract

In addition to the substantial amounts of available Earth Observation (EO) data, there is currently an increasing trend towards the acquisition of larger and larger EO data and image quantities from single satellites or missions, with multiple, higher resolution sensors and with more frequent revisiting. More sophisticated algorithms and techniques than those largely in use today are required to exploit this rapidly growing wealth of data and images to a fuller extent. The project “Survey and Assessment of Advanced Feature Extraction Techniques and Tools for EO Applications” (SURF) funded by the European Space Agency (ESA) will address these issues. The objective of SURF is to provide an overview of the current state-of-the-art Methods within feature extraction and manipulation for EO applications and to identify scenarios and related architectures for exploitation of the most promising EO feature extraction Methods. The task is to identify the most promising Methods to extract pertinent information from EO data on environment, natural resources and security issues. SURF aims at listing existing Methods with the final goal of identifying the three most promising Methods to be implemented in prototype solutions. The work includes the development of the concept for the evaluation and rating of Methods relative to the users needs for information, the maturity and novelty of the Methods, the potential for fusing data and the operational feasibility. Special emphasis will be made regarding the exploitation of state-of-the art image processing, pattern recognition and classification techniques.

Paper Details

Date Published: 5 February 2004
PDF: 10 pages
Proc. SPIE 5238, Image and Signal Processing for Remote Sensing IX, (5 February 2004); doi: 10.1117/12.523814
Show Author Affiliations
Mikael Kamp Sorensen, Geographic Resource Analysis and Science Ltd. (Denmark)
Michael Schultz Rasmussen, Geographic Resource Analysis and Science Ltd. (Denmark)
Henning Skriver, Technical Univ. of Denmark (Denmark)
Peter Johansen, Univ. of Copenhagen (Denmark)
Arthur Pece, Univ. of Copenhagen (Denmark)
Jesper Høyerup Thygesen, ROVSING A/S (Denmark)


Published in SPIE Proceedings Vol. 5238:
Image and Signal Processing for Remote Sensing IX
Lorenzo Bruzzone, Editor(s)

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