[Insight-developers] GaussianFilter::NormalizeAcrossScale not good for scale space analysis

[Luis Ibanez]

On Tue, Nov 23, 2010 at 11:21 AM, Bradley Lowekamp
<blowekamp at mail.nih.gov>wrote:

>
> My "n" refers to the order of the derivative not the dimension. This will
> perform exactly what is required for N-Dimensions of separated n-order
> derivatives.
>
>
>
> So, by applying the current normalization, (if only
> one Sigma per dimension) you end up with a
> Sigma^N normalization.
>
>
>
> We are talking about different Ns.
>
>

That clarifies my misunderstanding.

Can I suggest that we use "K" instead
of "N" for the order for the derivative ?


Scaling by:

                     Sigma^ K

where K is the order of the derivative,
makes sense.


I would suggest that we test this by
using an input image with an impulse

E.g. a image with all pixels set to zero,
and a single pixel in the center, set to
a nominal value (1000.0 for example ?).

In that way we should be able to verify
the correct numerical behavior for every
combination.

I'll take a closer look at your branch in
github.


     Thanks


          Luis
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