shirley@uicsrd.csrd.uiuc.edu (11/15/89)
I have a theoretical question for you rasterheads: How much filtering should we do on our images? Given a VERY high resolution display, we should certainly kill all freqencies greater than 2 pixel widths (especially in the vertical if you have an interlaced display). In the real world, we can still see the individual pixels, and sometimes this is useful. As an example suppose we have a function f(x) = black floor(x) is even white floor(x) is odd Further suppose we have a 1000**2 pixel display, and x is in pixel coordinates. This would have 1000 alternating vertical stripes of white and black, with each stripe one pixel wide. If we filter out the high freqency components then we'd have a grey screen. Intuitively it seems that we shouldn't filter. Now suppose we have the function f(x) = black floor((1.001*x) is even white floor((1.001*x) is odd This will give us 999 vertical stripes. If we area sample each pixel, then we'll have stripes on the left of the screen, fading into grey in the middle of the screen, going back to stripes on the right. This gives us a classic aliasing effect, and the party line is that we should filter. My question is whether this filtering is worth the trouble. Is the aliasing effect described above that bad in real world scenes? How often does this come up in real pictures, and how important is it? Thanks, pete shirley shirley@m.cs.uiuc.edu
gg10@prism.gatech.EDU (Galloway, Greg) (11/16/89)
In article <44100007@uicsrd.csrd.uiuc.edu>, shirley@uicsrd.csrd.uiuc.edu writes: > I have a theoretical question for you rasterheads: > ... > My question is whether this filtering is worth the trouble. Is the > aliasing effect described above that bad in real world scenes? How often > does this come up in real pictures, and how important is it? Rob Cook's "Stochastic Sampling in Computer Graphics" from ACM Transactions on Graphics, January 1986, is about the best reference on aliasing artifacts in point sampling systems. It discusses using a Monte Carlo method of randomizing your samples to substitute aliasing artifacts for noise which is less objectionable to the eye. It also discusses the pros and cons of analytic methods (filtering) versus discrete (sampling) methods. It should have the information you need. Greg Galloway Georgia Institute of Technology gg10@prism.gatech.edu