next up previous
Next: Multi-Resolution Up: Methods Previous: Joint Histogram Apodization

A Global-Local Hybrid Optimisation Method

Of the many different approaches to global optimisation we have investigated two strategies and combined them with a simple but fast local optimisation method to produce a hybrid optimisation method. The two strategies are: searching and multi-start optimisation. Our hybrid optimisation method (also described in [12]) is specifically designed for the problem at hand, using prior knowledge about the transformation parameters and typical data size (FOV, voxel size, etc.) to help make the method efficient. The method cannot guarantee that the global solution is found, but then neither can any other global optimisation method given a finite amount of time. Generally, only statistical ``guarantees'' are given, and these often require excessive run-times in order to be met. In contrast, our method is designed to give a reliable estimate of the global minimum given some time restriction (in our case, less than one hour on a moderately-powered standard workstation; e.g. registering two $ 1
\times 1 \times 1$ mm images typically takes 15 minutes on a 500MHz Pentium III). The method still uses a local optimisation method with a multi-resolution framework, and these are described in the next two sections, followed by descriptions of the global search and multi-start optimisation strategies employed.

Subsections
next up previous
Next: Multi-Resolution Up: Methods Previous: Joint Histogram Apodization
Peter Bannister 2002-05-03