[jtxx000]

The paper is old, but it's actually a fairly trivial application of signal processing techniques that have been well-understood since the 40s. For sub-pixel anti-aliasing, the approach would be to

1. Construct the underlying continuous field. This is just a function f(x,y) that returns one if the point is within the text and 0 otherwise.

2. Convolve f with an anti-aliasing filter. The filter could be tall and skinny to account for the fact that the horizontal resolution is 3x the vertical resolution.

3. Sample the resulting image at sub-pixel positions to produce the red, green, and blue values.

In the special case where the anti-aliasing filter is a box filter, this is exactly the same as computing the average for each subpixel. For the technique proposed in the article, the filter kernel would be the sum of six shifted impulses (Dirac deltas).

Anyways, I liked the article and wasn't trying to be critical of it. The convolution approach described above is of theoretical interest, but implementing it with any non-trivial kernel in real-time is almost certainly intractable. What I meant was that every implementation of anti-aliased vector graphics is a kludge, and it's pretty easy to coerce aliasing artifacts out of all of them using zone plates as inputs.

Edit: your article -> the article

[wtallis]

I certainly didn't mean to imply that the signal processing perspective was untenable with the modern world of actually-rectangular pixels, but what you describe is really a post-hoc shoehorning of square-pixel thinking into the signal processing framework. And you still haven't accounted for pixel-oriented font hinting or pixel-first design of bitmap fonts and graphics that gives leeway to the underlying shapes in order to maximize legibility when rendered onto a pixel grid. The signal processing perspective can offer some valuable insight, but it's a pretty bad choice as an overriding mode of thought for computer graphics.

(And I'm not the author of the article.)

[jtxx000]

Sure, for bitmaps fonts or pixel hinting the signal processing framework doesn't provide much insight. However, the word aliasing itself refers to a concept from signal processing, and in my opinion, it's easiest to think of anti-aliasing from the signal processing perspective.

For example, look at the images in [1] (also a rather old paper). The box filter results (i.e. where the pixel value is set to the average of covered area) are less than ideal.

[1] Quadrature Prefiltering for High Quality Antialiasing: http://www.cs.northwestern.edu/~jet/Publications/quadfilt95....

[a_e_k]

For what it's worth, you can find a nice detailed description of Microsoft's approach to sub-pixel anti-aliasing in "Optimal Filtering for Patterned Displays" [1]. There is also a follow-on, "Displaced Filtering for Patterned Displays" [2].

Interestingly, both papers feature an aliased zone plate. :-)

[1] http://research.microsoft.com/pubs/68972/optfilt.pdf

[2] http://research.microsoft.com/pubs/68631/sid2000.pdf