Were all the filters being compared with the same width? At the same width it will be softer, at a smaller pixel radius is where you can compare aliasing with the same visual sharpness as something like catmull-rom.
There were a variety of widths, it was one axis of the study. But I don’t remember the details, it is certainly possible you’re talking about something we didn’t test. Personally, at first I couldn’t even see the differences they were discussing.
Having studied graphics and signal processing for a few years in graduate school before that job, I thought I would be good at seeing the differences, and I was a bit shocked how good they were at it, and how not that good I was. :)
Truncating the Gaussian too closely though, and it’s not exactly a Gaussian anymore, you lose the best antialiasing properties. I can totally see how it will be sharper and more comparable to other popular filters. (Normalized & truncated at 1.1 radius is just slightly outside the 1 std dev line, right?)
Gaussian is my personal choice for large format prints of images with extreme aliasing problems.
My experience has likewise been that film DP’s have extremely impressive visual acuity, memory for color, etc. Talented artists often have developed whole sets of skills that the rest of us are unaware are even skills. In the same way a programmer might have thought about cache line false sharing as it affects memory hierarchy throughput, visual art often hides lots of expertise you cannot directly perceive, even as you can sense the quality of the whole.
I like to describe “learning to draw” as “installing a 3d modeling and rendering package on your brain, along with a decent collection of base models to modify”. It’s a complex skill set. If you start animating you get to add in a physics simulation. And you become conscious of so many little things that the layman only notices when you get it wrong.
> Having studied graphics and signal processing for a few years in graduate school before that job, I thought I would be good at seeing the differences, and I was a bit shocked how good they were at it, and how not that good I was. :)
IMO the best place to learn to see these distinctions is in careful photo printing (of the type where you spend >30m per image, and where “printing” here is being used in an old-school sense of “all of the manual steps to take a raw image from the camera and turn it into printed output”).
Spend a few months doing that for a few hours per week and your ability to see artifacts, textural details, fine differences in amount of edge contrast, etc. will shoot up. (Obviously the folks who spend 30 years on this are even better.)
Studying signal processing, optics, psychophysics, etc. is also useful for understanding what you are noticing, but it isn’t seeing practice.
The width of the filter is separate from how the gauss curve is used as a filter (and not everyone does it the same).
Using only one standard deviation cuts off a huge amount of the curve, ideally it would be cut off around the third standard deviation and normalized so that the value after the last would be zero.
