Yes, Nr. 8 on page 4 - let's see if we can deconvolve that!
That pattern will differ for each AA-filter and camera(type) combination. Some of the variables are, the thickness(es) of the crossed filter layers, their (individual and combined) orientation/rotation, and the distance to the microlenses/sensels.
(Un)fortunately, in practice, the PSF of a lens (residual aberrations+diffraction, assuming perfect focus and no camera or subject motion) plus an optical low-pass filter (OLPF) and the sensel mask and spacing will resemble
Gaussian rather than just the OLPF's PSF. As with many natural sources of noise, when several are combined then a (somewhat) modified Gaussian approximation can be made.
I have analyzed the PSF of the full optical system (different lenses + OLPF at various apertures + aperture mask of the sensels) of e.g. my 1Ds3 (and the 1Ds2 and 20D before that), and the effect a Raw converter has on the captured data
, and have found that a certain combination of multiple Gaussians does a reasonably good job of characterizing the system PSF. The complicating factor is that it thus requires prior knowledge to effectively counteract the effects.
Other complicating factors are defocus and camera shake (let alone subject motion).
The practical solution is to employ either a quasi-intelligent PSF determination based on the image at hand (or a test image under more controlled circumstances), or a flexible interactive interface system (some intelligent choices can be made to simplify things for the average user) that allows user interaction (human vision is e.g. quite good at comparing before/after images, especially when super-imposed).
There is a lot of ground to cover before simple tools are available, but threads like these serve to at least increase awareness.