Detail of the student project

Topic:High dimensional image similarity criteria for image registration
Department:Katedra kybernetiky
Announce as:
Description:We shall study image similarity criteria for multichannel (e.g. color) images, as well as to evaluate similarity based on texture and other local image descriptors. The tasks may include:

1. Implementing a high-dimensional nearest neighbor mutual information estimator for the ITK or Elastix frameworks and find suitable parameters and optimizer.

2.Compare the nearest neighbor and kernel-based entropy estimators.

3. Study local dimensionality estimation from sample data.

4. Study estimation of mutual information from quantized and noisy data.

5. Improve the stability and speed of the estimator.
Responsible person: Petr Pošík