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

[Francois Budin]

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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