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We know antialiasing best as "smoothing" the jagged edges that any digital editor will eventually happen across.  Why do we need to antialias, and where do aliasing artifacts come from in the first place?  The answer is a little mathy, but we'll bring it down to size.


The Basics
The concept of aliasing in video comes from, of all things, signals theory.  As we've discussed before, an image on a screen is basically a "quilt" of individual, rectangular** points of color called pixels.  But in the real world, images aren't just made up of individual points - instead, shapes have infinitely detailed, infinitely precise edges.  So the job of the computer is, essentially, to try to use the quilt of points to show our eye something similar to what we'd see if we were looking at something with infinite detail, like in the real world.

** - Incidentally, the pixels on your computer screen are square.  But the ones on your (NTSC) television aren't: they're rectangles that are skinnier than they are tall.  So representing NTSC video and graphics on computer screens becomes interesting, especially if you're using Photoshop - stay tuned until the Aspect Ratio B2B series for more.

Jagged Lines
When it comes to rectangular shapes, the quilt of pixels is perfectly as good as the real world - after all, the quilt is made up of perfectly rectangular points.  So even if you squint right up close at a few individual pixels representing vertical or horizontal lines, the boundary that you see between them will also be a perfect(ish) line.

However, if we start trying to draw round or diagonal lines using our quilt, we'll quickly run into problems.  If we try to approximate a nice, clean circle that's, let's say, a single pixel wide, we'll end up with something like the circle on the left:

That circle on the left?  That's seriously the best circle of those dimensions that you can approximate with solid pixels.  Photoshop said so.  So why does the one on the right look better?  Well, it comes back to the fact that we're trying to use our pixels to represent what the human eye would see if it were looking at something infinitely precise.  Notice how the circle at right looks kind of like you're squinting at a real circle.

The word "alias" means an assumed identity.  And that's what goes on when the computer tries to describe something like a circle one-for-one on a quilt of squares, like it did on the left-hand side: the shape that it chooses to draw might describe a circle, or it might describe the jaggedy island that it looks like, or it might describe a bunch of little lines and squares nearby to one another - any of these could be an accurate description for the image.

Antialiasing tries to make this less ambiguous.  Since the computer knows what a circle looks like with far more detail than it actually shows on-screen, it can pretend that it's your eye: it can "draw" a circle that's more detailed than it can display, and then "squint" at it to see what it more truly should look like to your eye.

When you look at the small antialiased circle on the right, it appears to be the same width as the small normal one on the left.  Why so?  Notice that only a few of the squares in the antialiased circle are completely as red as the squares on the left.  Long story short, if you scooped up the red spread out on either side of a point on the antialiased circle, then mushed it together into one pixel, it would still add up to one pixel of perfect red.  Smart things, these computers.

Anti-aliasing plays a whole different role in the context of 3D content and complex patterns (e.g. brick walls).  The technology basically solves those problems for us these days, although I have begun to notice Moire patterns in broadcast HD content.  If you're interested, I'm happy to write more about it - just drop me a note through the blue "contact us" box at right send me an email or leave a comment!.

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