Antwort: Matlab's imresize

Posted by Joachim Wesner on Sep 10, 2009; 1:57pm
URL: http://imagej.273.s1.nabble.com/Matlab-s-imresize-tp3691242p3691243.html

Hi,

even if there is ONE algorithm, implementation details might cause slight
differences....

What kind of differences do you see? What size of difference? Can you post
an example somewhere?

I assume you use FloatProcessor in ImageJ? On Matlab, what is the image
data type?

I could also imagine this depends WHERE exactly the pixel contents is
assumed to be located,
in the center of a "pixel box" or in some edge. This offset normally makes
no difference when reading/writing
 unscaled data,  but might make a difference when resizing by a
(noninteger?) factor!????

Just my 0,02$ (or 0.02€)

Sincerely

Joachim Wesner




                                                                           
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Hello,

Matlab's imresize and FloatProcessor's resize functions are giving
different
results when both are using bilinear interpolation [I didn't try the other
interpolation methods for comparison].

What could be causing this? Are they supposed to be different? I went
through the IJ source code, but I could not do the same in matlab [since I
got stuck in tformarray.m].

For your reference, I am shortly writing down what I am doing:

In Java,

*for(k=0;k<stackSize;k++)
{
    ImageProcessor ip = imp.getStack().getProcessor(k+1);
    ip.setInterpolationMethod(ImageProcessor.BILINEAR);
    ip = ip.resize(128, 128);
    stack.addSlice("NewImage", ip);
}
*
In Matlab,

*for k = 1:numberOfSlices
     NewImage(:,:,k) = imresize(squeeze(originalImage(:,:,k)),[128
128],'bilinear');
end*

I would appreciate any comments. Thank you very much.

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