The trick here is that the areas that have a lot of detail (her face, for example) contain less blue. If you use a color meter to inspect the areas around the girls face, you'll find that there is less blue light present. That makes sense, considering that our skin doesn't contain a lot of blue pigment. This fact is exacerbated by the fact that the author overlaps the channel samples in a way that places emphasis on the areas impacted the most.
Basically, the author fails to understand the additive color model. We don't notice the pixelation of the blue channel in this photo because the result of the alteration is to introduce a low-contrast color in to the photo where the aberration overlaps: yellow. If you look closely, you'll see that the areas where you see cyan and magenta in the red and green channels are replaced by yellow in the corresponding blue channel alteration. The effects are diminished by two factors: there isn't much blue luminance present to influence the other colors, and yellow contrasts poorly with most of the colors in the photo where we notice it (the hood is white).
If you were to take a color-neutral photograph and split out the RGB channels, you'd perceive the same level of detail in all channels.
EDIT: I'd kind of like to take back that last statement about perceiving the same level of detail in all channels. I don't know that you would, but that's not the primary thing that bugs me about the author's argument. My main point is that his argument is flawed, not his assertion. I don't know enough about human color perception to make that argument.