```There are several tricks for making this algorithm work better.  Removing
the mean is one of these.  Here is a recent blog that shows the importance
of these tricks.
Regards,
Steve

http://www.dsprelated.com/showarticle/52.php
```
```>Hi,
>
>In connection with pattern identification in images, cross-correlation
>between the image and a template matrix is often used. Is there any
reason
>why the means are substracted from the elements before the multiplying
them?
>If the only purpose is to detect similarity, the scaling seems
unessecery.
>
>
>
>

Actually, these calculations are applied to general cases. Image that you
two matrices which stand for two individual pictures. The number elements
of first matrix are range from 0 to 1, while the numbers elements of the
second matrix are range from 30 to 251. Maybe the pictures are captured
from exactly the same sense and content are completely the same, just with
different illumination etc. What you are supposed to do with these two
matrices, if you want to determine the similarity?

So normalization is always an important step for both pre-processing and
finalization.

```
```Simon Johan wrote:
> Hi,
>
> In connection with pattern identification in images, cross-correlation
> between the image and a template matrix is often used. Is there any reason
> why the means are substracted from the elements before the multiplying them?
> If the only purpose is to detect similarity, the scaling seems unessecery.

Subtracting the means is not the same as scaling. Some operations
(integration, for instance) are upset by a non-zero mean.

Jerry
--
Engineering is the art of making what you want from things you can get.
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```
```Hi,