Image Alignment
T.P Harte
image alignment/registration.
About all I know is that if you correlate two images and look for the maximum
on the 2D correlation surface, the max tells you the point in cartesian space
where the images are best aligned.
I suspect, somehow, that this is not the whole story and that there is
probably a literature out there on this topic.
Any pointers to the literature and source code to get an overview perspective
of the area would thus be appreciated.
Thomas.
t...@oz.usaw.bah.com
> I am looking for references/source code on the topic of
> image alignment/registration.
>
> About all I know is that if you correlate two images and look for the maximum
> on the 2D correlation surface, the max tells you the point in cartesian space
> where the images are best aligned.
>
> I suspect, somehow, that this is not the whole story and that there is
> probably a literature out there on this topic.
It depends on what you are trying to align,
a single point correlation will allow correction of
translation misallignment.
There is a real good discussion in the Manual of Remote Sensing.
Tim
Earl F. Glynn
news:7u0cv2$608$1...@pegasus.csx.cam.ac.uk...
> I am looking for references/source code on the topic of
> image alignment/registration.
> Any pointers to the literature and source code to get an overview perspective
> of the area would thus be appreciated.
Take a look at Section F, Image Registration, at
http://www.efg2.com/Lab/Library/ImageProcessing.htm
___
efg
Earl F. Glynn E-Mail: Earl...@att.net
Overland Park, KS USA
efg's Computer Lab: http://www.efg2.com/Lab
Thomas Sondergaard
> Any pointers to the literature and source code to get an overview perspective
> of the area would thus be appreciated.
>
"A Survey of Image Registration" by Lisa G. Brown - That's all I
remember from memory, but should be good enough for you to find it. I
think it's published through ACM.
Best regards,
Thomas
--
Arithmetic is being able to count up to twenty without taking off your
shoes.
-- Mickey Mouse
Paul Thompson
Here are two on-line chapters that you might like, reviewing the
different approaches to image registration, and their conceptual bases:
http://www.loni.ucla.edu/~thompson/ElasChpt.html
http://www.loni.ucla.edu/~thompson/PDF/no_pics_ElasChpt.pdf
and
http://www.loni.ucla.edu/~thompson/IVCJ_99.html
http://www.loni.ucla.edu/~thompson/PDF/IVCJ_99.pdf
Good luck! - Paul
--------------------
Paul Thompson, Ph.D.
Assistant Professor of Neurology, Dept. Neurology
UCLA Brain Mapping Division & Lab of Neuro-Imaging
Howard Hughes Medical Institute
73-360 Brain Research Institute
CHS-UCLA, Los Angeles, CA 90095-1769
thom...@loni.ucla.edu
http://www.loni.ucla.edu/~thompson/thompson.html
http://www.loni.ucla.edu/~thompson/thompson_pubs.html
T.P Harte wrote:
>
> I am looking for references/source code on the topic of
> image alignment/registration.
>
> About all I know is that if you correlate two images and look for the maximum
> on the 2D correlation surface, the max tells you the point in cartesian space
> where the images are best aligned.
>
> I suspect, somehow, that this is not the whole story and that there is
> probably a literature out there on this topic.
>
Sharon Simmons
If you would like to download a demo version of our image alignment
software, please visit our website at www.fairfield-imaging.co.uk
T.P Harte
: "A Survey of Image Registration" by Lisa G. Brown - That's all I
: remember from memory, but should be good enough for you to find it. I
: think it's published through ACM.
Brown, L.G. (1992) "A survey of image registration techniques",
ACM Computing Surveys, 24(4), pp 325--376.
Sebastien Durbec
> I am looking for references/source code on the topic of
> image alignment/registration.
>
> About all I know is that if you correlate two images and look for the maximum
> on the 2D correlation surface, the max tells you the point in cartesian space
> where the images are best aligned.
>
> I suspect, somehow, that this is not the whole story and that there is
> probably a literature out there on this topic.
>
> Any pointers to the literature and source code to get an overview perspective
> of the area would thus be appreciated.
>
> Thomas
Have a look with your browser to :
Registration by maximization of mutual information (near Kullback-Leiber
distance)
for a probalistic approach which is pixel and shape "non-dependant" (Wells &
Viola, Medical Imaging), really interesting.
Or more classical phase-registration with Fourrier Transform for Translation or
Fourrier-Melin Transform for homothetie, rotation ...etc... (There are a lot of
thesis in Belgium about this subject, but i don't no why !!!) (2D, a little bit
more complicated in 3D).
--
-------------------------------------------------------------------
2 Secrets to success: 1. Don't tell everyone what you know.
-------------------------------------------------------------------
Sébastien Durbec Email : s...@zh.steria.ch
Tel : +41 (0)1 298 50 88 (direct)
Steria Informatic SA/AG +33 (0)6 85 94 63 60 (mobile)
Militärstrasse 105 Tel : +41 (0)1 298 50 70 (office)
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Manoj Aggarwal
computing surveys, Vol. 24, No. 4, pp. 325-376, 1992
Sebastien Durbec <s...@zh.steria.ch> wrote in message
news:380F11AB...@zh.steria.ch...
Michael Jacobs
Hello Thomas,
The first question is what are you trying to align? For medical images
Currently, There are two major competing registration algorithms, these methods
are the AIR method (based upon the minimizing the ratio of the signal intensities
of the two images) or surface matching. Both have been shown to give very
reasonable results. After you do the registration, do you need to warp the
image? That answer is another area of research. Anyway, I have sent you a
reference list for your use. Good luck.
Michael Jacobs
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display aspects,” Eur. J. Radiol. 17 (1), 22-27 (1993).
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26(8) 1568-1578