The Truth About 2K, 4K and The Future of Pixels

Creative COW by John Galt

John Galt: “Pixel” is an unfortunate term, because it has been hijacked.

Historically, 2K and 4K referred to the output of a line array scanner scanning film, so that for each frame scanned at 4K, you wind up with four thousand red pixels, four thousand green and four thousand blue.

For motion picture camera sensors, the word “pixel” is kind of complicated. In the old days, there was a one-to-one relationship between photosites and pixels. Any of the high-end high definition video cameras, they had 3 sensors: one 1 red, a green and a blue photosite to create 1 RGB pixel.

But what we have seen particularly with these Bayer pattern cameras is that they are basically sub-sampled chroma cameras. In other words they have half the number of color pixels as they do luminance And the luminance is what they call green typically. So what happens is you have two green photo sites for every red and blue.

So how do get RGB out of that? What do you have to do is, you have to interpolate the red and the blues to match the greens. So you are basically creating, interpolating, what wasn't there, you're imagining what it is, what its going to be. Thats essentially what it is. You can do this extremely well, particularly if the green response is very broad.

Well 4K in the world of the professionals who do this, and you say “4K,” it means you have 4096 red, 4096 green and 4096 blue photo sites. In other words...

Creative Cow: 4000 of each. 4K.

[Laughter]

John Galt: Right.

But if you use the arithmetic that people are using when they are taking all of the photosites on a row and saying they're 4K, they are adding the green and the blue together and saying, “Oh, there are 4K of those, so it's 4K sensor.” Now actually, in order to get RGB out of a Bayer pattern you need two lines. Because you only have green plus one color (red) on one line, and green plus the other color (blue) on the other line. You then have to interpolate the colors that are missing from surrounding pixels. read more...