But if you shrink by 3, and your image is divisible by 3 does that
appear to introduce a bias as well?
Yes depending on the position of the edge. In this case I also expect a
bias when using a linear interpolation filter though.
I think the ShrinkImage implementation is fine but it would be nice to
have it stated in the documentation that a nearest neighbor
interpolation is used. It's say simple subsampling which is ambiguous to
me.
As for using it as default in the ImagePyramid filter I think this can
be cause for unexpected trouble and it would be helpful to mentioned in
the documentation that a nearest neighbor interpolation is used which
will lead to a shift in the image gradients. As it is now downsampling
with the the default setting Pyramid filter and then upsampling to the
original size results in such shifts. I expect that if i subtract the
original image from a downsampled image of the pyramid that I get
something that roughly looks like a second derivative. This is alignment
of "edges" is typically important in any multiscale approach where
computations are done at the coarser scales and then propagated to finer
scales (e.g. in registration you will create computational overhead by
forcing the registration to correct for the shift. In my application,
learning image features at multiple scales and their differences, this
shift does not actually matter all that much since the learning will
adapt to this shift but I think I loose some redundancies I could take
advantage of.).
For a general purpose Image Pyramid filter it might be useful to take
an (possibly weighted) average of all the pixels centers at the finer
scale that fall within the extent of a pixel at the coarser scale. For a
multiresolution schedule that is divisible this can be relatively
efficiently implemented.
-Sam
I have a fiter which does average a "shrink" region which can be
easily used in an external module[1]. Perhaps that would be more
appropriate for your current application.
This issue has been debated about before. I'd be curious as to what
you think of this [2] abandoned gerrit topic.
Brad
[1] https://github.com/blowekamp/itkBinShrink
[2] http://review.source.kitware.com/#/c/8179/
On Jul 18, 2013, at 10:54 AM, sgerber <[email protected]> wrote:
Hi Brad
Thank you for your feedback and taking the time to look at the
images. I am fairly certain that the "bias" is introduced due to the
subsampling strategy used in the ShrinkImageFilter, if an average
would be used the bias would disappear.
-Sam
On 2013-07-17 11:51, Bradley Lowekamp wrote:
Hello Sam,
I looked at the images you provided here:
http://www.cs.utah.edu/~sgerber/tmp/pyramids.zip [3]
in Slicer3D. I would agree that test1 from the RecursivePyramid
with
the shrink filter does not appear to align up correct. So you are
likely onto something.
What I have found useful for many of these types of geometric
filters
is to create an image of points of the physical location of center
of
the pixels, or a set of images if the filter in question doesn't
support the multi-component pixels. Then pass this through the
filter.
Aside from potential boundary conditions the the pixel values of
the
output should still be the physical location of the pixel in the
output. This can create useful and definitive tests.
Brad
On Jul 17, 2013, at 11:15 AM, sgerber <[email protected]> wrote:
Hi
RecursiveMultiResolutionPyramidImageFilter behaves significantly
different when using UseShrinkImageFilterOff() vs.
UseShrinkImageFilterOn(). The default, UseShrinkImageFilterOn(),
uses for subsampling a single pixel ("top right" corner) which
results, for piecewise constant images, in image gradients being
shifted in physical space. Is this intended? It's not the behaviour
I expected when I used this filter. It is also not documented in the
PyramidFilter documentation or the ShrinkImageFilter that this is
the subsampling method used.
Thanks
Sam
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