Isn't it crazy how the image where every other pixel is black (labeled "Without interpolating, we can clearly see we only have half the pixels") sort of looks t

Isn't it crazy how the image where every other pixel is black (labeled "Without interpolating, we can clearly see we only have half the pixels") sort of looks to have higher fidelity than the one after it, where the black pixels have been removed, which now looks pixelated? And yet both images have the exact amount of information, because all pixels that have been removed are simply black. The effect is so pronounced, that I wonder whether there wasn't any additional processing between the two images. Compare the window with the sky reflection between the two: In the image without black pixels, it looks distorted and aliased, while in the one with, it looks pristine. If actually only the black pixels have been removed (and the result nearest-neighbor scaled), I think the black pixel grid is a form of dithering, although neither random, nor the error diffusion kind one usually thinks of when hearing "dithering". There is no error being diffused here, and all added pixels are constant black. Maybe the black pixels allow the mind to fill in the gaps (shifting the interpolation that was also removed, prior to the black pixel image, to our brain, essentially). It is known that our brain interpolates and even straight makes up highly non-linear stuff as part of our vision system. A famous example of that is how our blind spot, the fovea where the optic nerve comes out, is "hidden" from us that way. The aliasing would "disappear" because we sort of have twice the amount of samples (pixels), leading to twice the Nyquist frequency, only that half of the samples have been made up by our vision system through interpolation. (This is a way simplified and crude way to look at it. Pun unintended.) But before jumping to such lofty conclusions, I still wonder whether nothing more happened between the two images...