Hello,
I use Lightroom for my photos, but also other software provide the "sharpening"
function to improve the images.
Usually the parameters are "amount", "radius" and "masking" (Lightroom has one
more).
I always wondered how to choose the "radius" effectively, since just looking at
the result may not be the best option.
I found this page with a suggestion and an explanation of the value and a brief
history of the unsharp mask (Joachim and Michiel and the other people
experienced in the development of film probably already know that):
http://photo.stackexchange.com/questions/1370/unsharp-mask-what-do-the-parameters-do
I quote the useful part:
-----
The unsharp mask is an old technique that has been used in darkrooms long
before computers were capable of processing images.
The original process consists of two exposures; first you create an unsharp
mask by making a contact copy on low-contrast positive film, but with a
distance between the original and film (and sometimes a diffusing plastic
sheet) so that it becomes blurred. When you put the blurred positive and the
negative together and make an exposure on paper, the positive cancels out some
of the light from the negative. As the positive is blurred, it lets through
more of the small details, which makes the image appear sharper.
Two of the parameters directly correspond to this old method;
The radius is how much the positive is blurred.
The amount is how much the positive is exposed.
The threshold has been added to enable you to exclude low-contrast edges from
the sharpening.
A good baseline for the radius is around 0.1 mm. For an image that is to be
viewed on a screen, which is about 100 ppi, it translates to a radius of 0.5.
For an image that is to be printed at 300 ppi, it translates to a radius of 1.5.
-----
It's not clear to me how I get the radius from dpi and mm (0.1mm @100 dpi is
2.54 pixels, not 0.5), but these guidelines can be useful.
Also, working with amount = 100-150% and playing with the radius until it looks
ok, then reducing the amount to reasonable values is another suggestion to
obtain the best images.
As additional info, this article is very informative (and technical):
http://clarkvision.com/articles/image-restoration2/
Olaf
