1. Computationally intensive methods
Ercan E. Kuruoglu
CNR – Istituto di Scienza e Tecnologie dell’Informazione
Pisa, Italy
Muscle Joint WP5-WP7 Focus Meeting, Rocquencourt, December 2005

2. introduction MCMC Particle filtering What we can offer
Overview
introduction
MCMC
Particle filtering
What we can offer
What we look for

3. Numerical Bayesian Techniques
Bayesian methods frequently involve integrals of
Averaging
Marginalisation
Normalisation
which are difficult to evaluate.
Therefore numerical integration techniques are adopted.

4. Alternative Statistics
In most applications of statistical signal and image processing classical statistical measures, i.e. second order statistics is used
Instead a wide variety of other statistics exists
Higher order statistics
Fractional lower order statistics
Log statistics
Extreme value statistics
We would like to explore the potentials of log statistics and extreme values statistics in image, video and multimedia problems

5. Markov Chain Monte Carlo
Samples from a pdf with clever Markov Chain moves
Economic in terms of samples needed for describing a pdf
Analytical difficulties are surpassed

6. Particle Filtering
In various real life applications, the signal is non-stationary, and MCMC being a batch processing technique falls short of following non-stationarity
Wiener filter
Kalman filter
linear observations (h)
Gaussian observation noise (n)
linear state process (f)
Gaussian process noise (v)

7. Applications we have worked on
Source separation
Speckle filtering in synthetic aperture radar images

8. Astrophysical source separation

9. Original sources : CMB Galactic Syncrotron Galactic Dust
Observed maps: 30 Ghz Ghz Ghz

10. SAR speckle filtering

11. Preliminary results with a special case of Particle filter
Optical image
SAR image 5 looks
Gamma Filter
Particle Filter
Gençağa et. al.

12. What we would like to share with partners
Expertise in MCMC and Particle filtering
Expertise in extreme value statistics, alpha-stable models (impulsive and nonsymmetric data models
Particle filtering code
For model selection problems: Reversible Jump MCMC code