BIOMEDICAL IMAGING GROUP (BIG)
Laboratoire d'imagerie biomédicale (LIB)

A Pyramid Approach to Sub-Pixel Image Fusion Based on Mutual Information

P. Thévenaz, M. Unser

Proceedings of the 1996 Third IEEE International Conference on Image Processing (ICIP'96), Lausanne VD, Swiss Confederation, September 16-19, 1996, vol. I, pp. 265–268.

We investigate aspects of multi-modal image registration based on a new criterion named mutual information (or sometimes Shannon information). This criterion is intensity-based and requires no landmarks; hence, its application can be automated without resorting to segmentation. We present a form amenable to derivation with respect to the geometric transformation parameters (here: affine transformation). This form involves Parzen windows; we explore the dependence of the registration accuracy on these windows and propose that they be tuned to each resolution level in a pyramid approach. We conduct experiments and show that both the window width and the number of windows is relevant. In addition, we show that it is beneficial to use a spline-based high-order interpolation scheme for applying the geometric transformation. 

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