[ITK-users] [ITK] Normalized Cross Correlation returns perfect alignment with images not even overlapping

[Francois Budin]

Hello Andrew,

Another thing you can look at is if your transform parameters ratios are
set to reasonable values. You typically have a ratio you can set between
rotation, translation, scaling. If these are not set to appropriate values,
the final transform could be wrong.
In your case, it sounds like you are already performing the translation as
an initialization. Maybe you can modify your parameters so that it performs
mostly a rotation.

Hope this helps,
François

On Tue, Apr 11, 2017, 14:07 Dženan Zukić <dzenanz at gmail.com> wrote:

> Hi Andrew,
>
> it is good to use such additional constraints when possible. But you also
> have to initialize the transform somehow, otherwise it might get
> auto-initialized to all modifiable parameters being equal to zero. That is
> usually a bad initial transform - hence Francois' suggestion.
>
> Regards,
> Dženan Zukić, PhD, Senior R&D Engineer, Kitware (Carrboro, N.C.)
>
> On Tue, Apr 11, 2017 at 2:02 PM, Andrew Harris <aharr8 at uwo.ca> wrote:
>
> Hello Francois and Dženan,
>
> Because of the way the images were captured, there is a known common point
> of overlap, so we set the centre to that point in the expectation that the
> transform would rotate and translate about that point when the registration
> is run.  Have I misunderstood the design or is that what should be
> happening?
>
> --
>
> AH
>
>
>
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> On Tue, Apr 11, 2017 at 9:00 AM, Francois Budin <
> francois.budin at kitware.com> wrote:
>
> Hello Andrew,
>
> Did you try to initialize the registration with [1] for example?
> If the images do not overlap at all at the beginning of the registration,
> the algorithm might only do what Dżenan said, match black pixels.
> Initializing the transform should help.
>
> Hope this helps,
> Francois
>
> [1]
> https://itk.org/Doxygen/html/classitk_1_1CenteredTransformInitializer.html
>
> On Tue, Apr 11, 2017 at 8:36 AM, Andrew Harris <aharr8 at uwo.ca> wrote:
>
> In the image mask, the parts we want to include in the calculation are
> bright and the parts that we want to exclude are dark, is that the opposite
> of what it should be?
>
> --
>
> AH
>
>
>
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> On Thu, Mar 30, 2017 at 7:25 PM, Dženan Zukić <dzenanz at gmail.com> wrote:
>
> Hi Andrew,
>
> your masks might be inverted. If NCC gets all black pixels in both images,
> the correlation will be perfect.
>
> Regards,
> Dženan
>
> On Thu, Mar 30, 2017 at 2:13 PM, Andrew Harris <aharr8 at uwo.ca> wrote:
>
> Hi, I'm hoping someone can guide me toward an explanation of this.  I run
> my pipeline on various ultrasound image sets and get an NCC between 0.65
> and 0.8 for good alignments, but on some sets the NCC returns 1.0 when the
> images aren't even overlapping.  I have the black areas of the image masked
> out, and have even tried cranking up the threshold to be sure the darker
> areas aren't being included to no avail.  Any thoughts?
>
> --
>
> AH
>
>
>
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