Modeling and Information Processing
Image processing and data fusion
Objectives
- To design innovative methods and concepts in signal and image processing for dynamic or decision making systems,
- To design information processing and fusion methods for heterogeneous and distributed systems,
- To contribute to the design of complex systems in which the information processing part is a dimensioning factor for performance and cost reduction
Context
Future aerospace systems (vehicles and associated ground segment) afford an increasing place to software components and information technology. Recent progress in these areas has lead to major conceptual breakthroughs in the fields of autonomy, analysis and decision making and more generally the control of information.
Within this context, the DTIM is carrying out research activities in image processing and data fusion applied to the aerospace context. The objective is to investigate and promote technological advances in capabilities for a wide range of applications: computer aided navigation of autonomous machines, computer aided analysis and identification for surveillance and observation systems and computer aided design of distributed multi-sensor systems, etc.
These research activities are oriented toward the understanding and the incorporation of those system aspects which are primordial for ensuring the satisfaction of requirements and the overall optimization, in particular, of cost reduction. They are split into 3 main complementary topics.
Main topics
- Estimating non-linear numerical models with robust methods
- Interpreting scenes by implementing learning techniques and identifying perceptual models
- Fusion information by studying the aspects related to the modeling of knowledge and the management of heterogeneous sources within a distributed architecture
Areas of activity
- ADO, data associations
- ANAIS 3D, analysis in 3D imaging
- AR-SYS, systems architecture
- ATR, automatic target recognition
- DOI, detecting objects of interest
- EMI, estimating image movements
- GPU for Image Processing and Vision
- INDEX, image indexing
- MC2, modeling and capitalizing knowledge
- SAM, structure and movement
- SR, super-resolution
- TAF, advanced fusion techniques
- TAP, advanced particulate techniques
- TRACK, tracking
