[mfabbri77]

As pointed out by Raphlinus, the moire pattern in the Siemens star isn't such a significant quality indicator for the type of content usually encountered in 2D vector graphics. With the analytical coverage calculation you can have perfect font/text rendering, perfect thin lines/shapes and, by solving all the areas at once, no conflating artifacts.

[dahart]

Raph made an argument that Box is good enough for lots of things, which is subjective and depends entirely on what things you’re doing, and how much you actually care about quality.

You are claiming it’s the best possible. Box filter is simply not the best possible, and this fact is well understood and documented.

You can relax your claim to say it’s good enough for what you need, and I won’t disagree with you anymore. Personally, I’m sensitive to visible pixelation, and the Box Filter will always result in some visible pixelation with all 2D vector graphics, so if you really care about high quality rendering, I’m very skeptical that you really want Box filtering as the ideal target. Box filter is a compromise, it’s easier & faster to compute. But it’s not the highest quality. It would be good to understand why that’s the case.

* Edit to further clarify and respond to this:

> With the analytical coverage calculation you can have perfect font/text rendering, perfect thin lines/shapes and, by solving all the areas at once, no conflating artifacts.

You cannot get perfect font or text rendering with a Box filter, and you will get some conflating artifacts. They might be very slight, and not bothersome to most people, but they do exist with a Box filter, always. This is a mathematical property of Box filtering, not a subjective claim.

[yorwba]

Why do conflation artifacts always exist with a box filter? AFAIK conflation artifacts are a product of the compositing process, not the filtering process.

If you have two non-overlapping shapes of the same color covering the plane and use a box filter on the first shape to sample a pixel on the boundary, and then use the same box filter on the second shape, and then composit them with alpha blending, you get a conflation artifact along the boundary where the background bleeds through.

But if you use the fact that the shapes are non-overlapping and sum their contributions instead, the artifact disappears, while still using the same box filter.

[dahart]

It’s because sampling artifacts never disappear with Box. The reason is the high frequency aliasing is introduced by the filtering. It’s because the Box itself has infinite frequency response that you cannot eliminate the artifacts, it’s not possible. This is why all other, better filters fade their weight smoothly to zero at the support boundary.

You can see this with a single sharp edge, it doesn’t need to involve multiple polygons, nor even vector rendering, it happens when downsampling images too.

[raphlinus]

These are sampling artifacts, but I believe yorbwa is correct in distinguishing these from conflation artifacts, as defined in Kilgard & Bolz. I think of the latter as compositing not commuting exactly with antialiasing (sampling). You only get conflation artifacts when compositing multiple shapes (or rendering a single shape using analytical area when the winding number is not everywhere 0 or 1), while you definitely see aliasing when rendering a single shape, say a Siemens star.

[dahart]

Okay, that’s fair. I’m misusing the term ‘conflation’ in that sense. I was trying to make the point that compositing two wrong answers yields a wrong answer, but I stand corrected that it’s not the compositing that’s introducing error, it is the sampling + box-filtering.

[raphlinus]

I don't see how you can support the claim of perfect thin line rendering, it's visibly just not very good. So box filtering logically can't possibly be the best possible quality.

Can we make a magical adaptive filter which resembles box filter for half-planes, a tent filter for thin lines, Mitchell-Netravali or oblique projection for natural images, and Gaussian when filtering images for which high frequency detail is not important? Perhaps, but that feels like advanced research, and also computationally expensive. I don't think you can claim "perfect" without backing it up with human factors data really demonstrating that the filtered images are optimum with respect to perceived quality.

[nyanpasu64]

I wonder if the ideas behind GIMP's new nonlinear resampling filters (NoHalo and LoHalo, and eventually more https://graphicdesign.stackexchange.com/q/138059) may translate to vector rasterization in some form (though here we're translating continuous to discrete, not discrete to continuous to a differently spaced discrete).