Nicholas Dowson at the University of Surrey | |

## Mutual Information## IntroductionMutual Information was originally devised by Shannon, as a
method to measure the information shared between two signals
with discretised amplitudes over a period of time. It is a
simple extension to consider discretised Mutual information is measured by obtaining a joint histogram of intensities of the overlapping regions between a template image and a reference image, before applying the following mathematical operation: I = \sum_{r,t} p_{rt} log( \frac{p_{rt}}{p_r p_t} )
## ObjectiveTo use mutual information to track small image patches. ## DifficultiesThe problem with small image patches is that the are often too small to obtain a fully populated histogram, the estimate of MI information is often incorrect.
As the position of the template relative to the reference
image changes, the various Mutual Information values describe
a Many methods exist for measuring Mutual Information. Some of these cause the position of the maximum to shift, making the final solution inaccurate. How is this prevented, and which method should be used? Most histogramming methods also ignore the structure of the image. This throws away important information, inherent to the data. Using the structure would give more accurate results. ## Our contributionWe have placed all the methods of Mutual Information into a single mathematical framework and critically compared them. For more information read this.
We have developed a method, called |