Hi Joel,<div><br></div><div>Aliasing artifacts appear only with nearest neighbor interpolation. Linear interpolation should be enough to avoid them (higher order interpolations also). And by doing a low-pass filtering, you are effectively destroying part of information in the image. However, depending on what will you be doing next with that image, low-pass filter might be justified.</div>
<div><br></div><div>Regards,</div><div>Dženan<br><br><div class="gmail_quote">On Fri, Jun 11, 2010 at 13:08, Joel Schaerer <span dir="ltr"><<a href="mailto:joelthelion@laposte.net">joelthelion@laposte.net</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;"><br>
Hi Dan,<br>
<br>
Thanks for your answer. I've already looked at that paper, but it only<br>
considers the choice of the interpolation function. My understanding is that<br>
for image downsampling, regardless of the interpolation function you use,<br>
you have to apply a low-pass filter to the image prior to resampling in<br>
order to avoid aliasing effects. My question is about this low-pass<br>
filtering step, not the interpolation function.<br>
<div class="im"><br>
<br>
<br>
Dan Mueller-2 wrote:<br>
><br>
> Hi Joel,<br>
><br>
> You may be interested in the following paper:<br>
><br>
> <a href="http://www.imagescience.org/meijering/publications/download/miccai1999.pdf" target="_blank">http://www.imagescience.org/meijering/publications/download/miccai1999.pdf</a><br>
> @inproceedings{Meijering1999a,<br>
> Author = {E. Meijering and W. Niessen and J. Pluim and M. Viergever},<br>
> Title = {Quantitative Comparison of Sinc-Approximating Kernels for<br>
> Medical Image Interpolation},<br>
> Booktitle = {Proceedings of Medical Image Computing and<br>
> Computer-Assisted Intervention (MICCAI)},<br>
> Page = {210--217},<br>
> Publisher = {Springer},<br>
> Volume = {1679},<br>
> Year = {1999}<br>
> }<br>
><br>
><br>
><br>
<br>
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