Conclusion

• We have presented a variational model based on level set formulation for image classification. The level set formulation is a way to represent regions and set of interfaces with a continuous function defined over the whole support of the image. The minimization of the functional leads to a set of coupled PDE's which are considered through a dynamical scheme. Each PDE is guiding a level set function according to internal forces (length minimization), and external ones (data term, no vacuum and no region overlapping). Results on both synthetic and satellite images are given.
  
  
• Further work will be conducted to deal with the estimation of the class parameters (unsupervised classification). We also envisage to extend this model to multispectral data (with applications to multiband satellite data and applications to color imaging).
  
  
• More details can be found in the research report.

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