On Jan 11, 2012, at 6:21 PM, Michael wrote:
Okay thanks guys!
I was actually looking for image processing libraries in R.
Specifically, I am looking for something like "filter2d" for
images(pixels)...
(speed is not a concern for me, since my images are really small,
200x200,
etc.)
And in fact, these are not images, these are 2d matrix numbers(i.e.
numbers
in a matrix format), I just wanted to smooth them.
Any more pointers?
Besides the huge amount of spatial regression material that you should
have found by looking up links from the 'spatstat' citation (and the
Geospatial Task View: http://cran.r-project.org/web/views/
Spatial.html), you should consider looking for packages and websites
the deal with functional MRI (fMRI). I also think there may be value
in looking at package 'locfit' and the 'mgcv' package, although they
may need special coercion to apply the kernels you expressed interest
in using.
On my machine this brings up the biOps package:
??"image processing"
And this is the same search with RSiteSearch
201 hits from:
http://search.r-project.org/cgi-bin/namazu.cgi?query=%22image+processing%22&max=100&result=normal&sort=score&idxname=functions&idxname=Rhelp08&idxname=Rhelp10&idxname=Rhelp02
--
David.
Thanks a lot!
On Wed, Jan 11, 2012 at 5:18 PM, Bert Gunter
<gunter.ber...@gene.com> wrote:
?loess ## in base R
does 2d filtering , though it's not a Gaussian one
-- Bert
On Wed, Jan 11, 2012 at 3:00 PM, Rolf Turner <rolf.tur...@xtra.co.nz>
wrote:
On 12/01/12 09:17, Michael wrote:
Hi all,
I am looking for a command for doing 2D filtering (rectangular or
Gaussian) in R...
I have looked at ksmooth, filter and convolve but they seem to be
1D...
Any thoughts?
Thanks a lot!
I'm not sure what you really need/want to do, but you might have a
look
at "smooth.ppp" (and possibly "density.ppp") from the "spatstat"
package.
cheers,
Rolf Turner
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--
Bert Gunter
Genentech Nonclinical Biostatistics
Internal Contact Info:
Phone: 467-7374
Website:
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David Winsemius, MD
West Hartford, CT
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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