Yes and since nearest neighbor corresponds to a sensor pixel only sensitive at a single point and binning is like a pixel of uniform sensitivity across the whole pixel area we can conclude that both these extremes are not the best choice. The optimum filter shape of course depends on the priorities you have.
I understand you see aliasing with point sampling and with area sampling as two aspects of the same effect. It does not matter for the my main hypothesis though: that an improved sensor design with respect to sensitivity across the pixel area will diminish aliasing and therefore reduce the need for an additional optical low pass filter. I see now that my initial idea that aliasing could be completely avoidable this way is not right but it still seems to make quite a difference.
Adjusting sensitivity across the pixel area will not help one little bit. Full area sampling is the very best a pixel can do with respect to aliasing performance. If you diminishing that in any way, aliasing will increase, not decrease. You can look at individual artificial examples that might, for that example, show better or worse performance, but that is the nature of aliasing - you will get frequency combinations that cancel out to mid grey, for instance, but even in the real world, and even with test charts, they're never perfectly aligned or uniform.
Filters work among groups of pixels, and that is why they can perform better. Optical filters spread the light which would touch one pixel over many pixels, and that is why they can reduce aliasing.
Graeme
