Re: Scientifically Based Presharpening for Enlargement
- From: davem@xxxxxxxxx (Dave Martindale)
- Date: Wed, 17 May 2006 18:24:21 +0000 (UTC)
"aruzinsky" <aruzinsky@xxxxxxxxxxxxxxxxxxxx> writes:
See:
http://www.interpolatethis.com/phpBB2/viewtopic.php?t=489&sid=5cc703c5751e675312819bfcb0c8ab94
Is my explanation of the concept clearly written? Please, make
suggestions on how to make this more clear to the general public.
A couple of suggestions:
1. If the main point of the page is implementing a method from a paper,
include a one-paragraph summary of that method in your web page. I'll
use that summary to decide whether I want to read the full paper, and it
will also serve as a substitute if the site with the full paper is
temporarily down.
2. As someone else pointed out, your examples are horrible. The
discussion talks about how images from a sensor are not point sampled,
they are effectively convolved with a small box (the area of a sensel)
before being measured. So show us an example of an image that is either
*direct from a sensor, with no processing applied*, or at least a
simulation of such an image. (For example, you could take a much higher
resolution image and convolve/downsample it to get your example).
What you have on the page at the moment shows really horrendous
sharpening artifacts (halos) as well as compression artifacts that
completely overwhelm the small difference between the two cases that you
are trying to show. Your starting images should be uncompressed and
unsharpened.
Also, if the "data dependent Lanczos" filter is what's responsible for
the weird wave-like textures in the road surface at the bottom of the
image, don't use this filter! Adding artifacts that weren't there in
the original is generally a bad idea, and especially bad in something
that's supposed to be an example. Why not use bicubic polynomial
interpolation, which (a) is familiar to many people, and (b) doesn't
create such artifacts. Yes, it doesn't preserve high frequencies as
well as Lanczos, but you should still be able to see the difference
between the images with and without presharpening applied, and that's
the point of the example.
3. You might address why the sharpening should be a preprocessing step.
If the sharpening is a linear filter, and interpolation is a linear
filter (and most popular interpolation methods are linear) then it
should not matter what order you perform them in - as long as you deal
with the change in magnification for the sharpening step. You might
even find a way to merge the sharpening into the interpolation.
On the other hand, if the interpolation filter is actually nonlinear,
then that's a reason why the sharpening needs to be a preprocess.
Dave
.
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