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Contenu archivé le 2022-12-23

Information Technology for Remotely Sensed Data Analysis Based on the System Integration of Multiscale Conceptions

Objectif

Research Objectives:
The global objective of project is to create the conceptual, methodological and theoretic foundation for information technology of remotely sensed data processing and analysis based on the on the system integration of multiscale conceptions:
continuous wavelet analysis,
discrete wavelet transform (WT),
fractal sets and
recursive scannings.
Proposed information technology allows to:
1. decrease the threshold of hidden signal detection by several times;
2. detect the signals with unknown form;
3. solve the problems connected to incomplete knowledge of signal, non-stationary, non-markovian and singular noises;
4. improve the performance of sub pixel signal detection and estimation in case of limited spatial and temporal resolutions of sensors.
The main application area of the developed techniques is processing and analysis of remotely sensed data. The developed techniques can be also effectively used for processing of astrophysical, biometric, biomedical images and geophysical data. Key activities of this research project are the development of the appropriate methods and algorithms in the frame of a new information technology for processing and analysis of remotely sensed data. This includes research activities in the following areas: segmentation and filtering of images obtained under conditions of prior uncertainty and noise irregularity, particularly in the frame of wavelet and fractal analysis; signal detection and estimation based of diffractive optical elements (DOE) and spectral analysis.
The following research results are expected:
•numerical evaluation of fractal characteristics for certain classes of satellite images;
•determination of the correlation properties and fractal characteristics on recursive scannings;
•mathematical models of noise with specified fractal characteristics (for signal detection and recognition);
•algorithms for anomaly detection based on wavelet transform;
•algorithms for anomaly detection and its boundary estimation using nonparametric statistic methods;
•algorithms of image segmentation by Change Point of Fourier spectrum using spline approximation of boundaries;
•methods and algorithms for designing diffractive optical elements and algorithms for digital processing of the derived design information; simulation of operation of DOE-aided systems and ecological assessment of multi-spectral images;
•parameterization of fabricated diffractive optical elements for analysis of remotely sensed data; results of experimental testing of the DOEs.

Appel à propositions

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Régime de financement

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Coordinateur

University Technische Universitat Dresden
Contribution de l’UE
Aucune donnée
Adresse
Mommsenstrasse
01062 Dresden
Allemagne

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Coût total
Aucune donnée

Participants (4)