Yes, I wouldn't get too gung-ho about declaring raws as non-images, either. Why reach for the binary definitions, when nuance does a much better job?
I like to think in terms of what happens when we stretch the parameters. For example, if a monitor had enough resolution or you stood far enough away from it, you could actually see the CFA pattern go extinct, whether your display is monochrome or color. So as far as CFA is concerned, it may only be an issue when we are magnifying the pattern too much, just like when we look at a printed image or a monitor screen under a microscope, and see dither patterns or separate little red, green, and blue rectangles; it is just a matter of degree. You could drop 2 out of 3 color channels just like a CFA in each pixel in a quality, realistic sRGB image, and if you step back far enough, the CFA pattern will disappear, and the image will simply seem a little too green and a bit too dark, but varying the brightness of pixels could get around that, and there are many monitors now that can give high pixel output, to compensate.
We could throw a convolution of
0.25 0.25 0.00
0.25 0.25 0.00
0.00 0.00 0.00
on your image, and the CFA effect vanishes, or just swap neighbor pixels randomly, and you get a noise dither instead of a CFA.
Perhaps it would be better to ask how realistic an "alleged" image is, than to ask if it is really an image.